EP3384688B1 - Successive decompositions of audio filters - Google Patents
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- EP3384688B1 EP3384688B1 EP16815620.6A EP16815620A EP3384688B1 EP 3384688 B1 EP3384688 B1 EP 3384688B1 EP 16815620 A EP16815620 A EP 16815620A EP 3384688 B1 EP3384688 B1 EP 3384688B1
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- H04S—STEREOPHONIC SYSTEMS
- H04S7/00—Indicating arrangements; Control arrangements, e.g. balance control
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- H04S7/303—Tracking of listener position or orientation
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Definitions
- the present invention relates to the field of the restitution of sound data.
- telecommunications terminals in particular mobile, for which it is envisaged a sound reproduction with a stereophonic listening system (a headset for example) allowing the listener to position the sound sources in space.
- a stereophonic listening system a headset for example
- the invention uses invariant and stationary linear systems that can be characterized by a set of filters depending on a direction between the sound source and one of the listener's auditory canals.
- This set of filters represents the directivity of the system. Filters can be represented in their time (as an impulse response) or frequency (as a transfer function) form.
- an individual or an artificial head with a microphone at the entrance to each auditory canal are particular cases of such an invariant and stationary linear system.
- the system can be characterized by its transfer functions, specific to each individual.
- the transfer functions define the spatial hearing characteristics of the individual by taking into account in particular the reflections linked to his morphology.
- the transfer functions are classically called transfer functions of the HRTF type for “ Head Related Transfer Function ”, when the filters are given in the frequency domain, and HRIR for “ Head Related Impulse Response ”, when the filters are given in the time domain. . It is possible to go from one representation to another by a Fourier transform.
- HRTF transfer functions are therefore a set of complex values. It is possible to return to real values by taking their respective moduli: we thus obtain the moduli of the HRTF.
- the invention can be generalized to the directivities of systems having different shapes and / or numbers of sensors (for example a mobile telephone with 3 microphones). Without prejudicing the generalization of the invention to any linear system that can be characterized by ORTFs, and in order to facilitate understanding of the invention, the particular case of DTF transfer functions is considered hereinafter. In fact, it is possible to pass from the DTF transfer functions to the HRTF transfer functions by calculating minimum phase filters associated with the DTF transfer functions and by adding a delay to them modeling the propagation delays between the capsules (inter-aural delay by a human ). The personalization of these delays is obtained by other techniques well known and not described here.
- HRTF-type transfer functions One technique using HRTF-type transfer functions is binaural synthesis. This technique is based on the use of so-called “binaural” filters, which reproduce the acoustic transfer functions between the sound source (s) and the auditory canals of the listener. These filters are used to simulate auditory localization cues that allow a listener to locate sound sources in a real listening situation.
- the techniques linked to binaural synthesis are therefore based on a pair of binaural signals which feeds a reproduction system.
- the two binaural signals can be obtained by signal processing, by filtering a monophonic signal by binaural filters which reproduce the properties of the acoustic propagation between the source placed at a given position and each of the listener's ear canals.
- Binaural synthesis can be used for different reproductions such as, for example, a reproduction by means of a headset with two earphones, or by means of two loudspeakers.
- the goal is reconstruction a sound field at the level of the listener's ears practically identical to that induced by real sources in space.
- Binaural filters take into account all the acoustic phenomena which modify the acoustic waves in their path between the source and the auditory canals of the listener. Acoustic phenomena include in particular diffraction from the listener's head and reflections on the auditory pinna and upper torso of the user.
- a quality binaural synthesis therefore relies on binaural filters which best reproduce the acoustic coding that the listener's body naturally produces, taking into account the individual specificities of his morphology.
- the binaural filters represent the acoustic transfer functions or HRTF type transfer functions which model the transformations generated by the listener's torso, head and pinna on the acoustic signal coming from a sound source.
- HRTF transfer functions carry the acoustic imprint of the morphology of the individual on which they were measured.
- the HRTF transfer functions are obtained during a measurement phase.
- a selection of directions which cover more or less finely the whole of the space surrounding the listener is fixed.
- the left and right HRTF transfer functions are measured using microphones inserted at the entrance to the listener's ear canals.
- a listener-centered sphere is defined in this way.
- the measurement must be carried out in an anechoic chamber, or an anechoic chamber, so that only the reflections and acoustic phenomena linked to the listener are taken into account.
- M directions we obtain, for a given listener, a database of 2M HRTF type transfer functions (because two right and left auditory channels) representing, for each auditory canal, each of the positions of the sources. .
- Some individuals thus spend long hours in the laboratory in order to have the acoustic signature associated with their physiognomy analyzed in detail, as well as their ability to perceive sound space in three dimensions. These individuals then benefit from binaural listening shaped from the analysis results, offering comfort and a high quality sound impression.
- a first approach consists in calculating the filters on the basis of the acquisition of the listener's morphology and in particular of his flag.
- I Wen Zhang et al. thus propose to decompose an HRTF transfer function on a basis of independent functions (" Efficient Continuous HRTF Model Using Data Independent Basis Functions: Experimentally Guided Approach ", IEEE Transactions on Audio, Speech and Language Processing, vol. 17, no. 4, May 1, 2009, pages 819-829 ).
- Personalization can also be based on the transformation of non-individual HRTF transfer functions extracted from a database including the morphologies associated with HRTF transfer functions ( "Individualization of spectral indices for binaural synthesis: research and exploitation of interindividual similarities for the adaptation or reconstruction of HRTF", Guillon, P, PhD Thesis, University of Maine, Le Mans, France, 2009 ; see also the patent FR 2958825 ).
- the transformation of the HRTF transfer functions to adapt them to a given individual is then controlled by the comparison of the morphologies of the original flag from the database and the target flag of the given individual. This comparison is based on a technique of matching the three-dimensional meshes of the pavilions. Another method consists in using morphological parameters to create or deform a three-dimensional mesh, which will then be used for a detailed calculation and a numerical simulation of the HRTF transfer functions of the individual, by finite elements of border for example. It is also possible, from the morphological parameters of a given individual, to search in a database a third individual with similar morphological parameters.
- One method of acquiring pinna morphology is to use a three-dimensional scan, but this method is sometimes problematic as it requires both specific hardware and implementation.
- the first approach consists in studying the capacity of the auditors to appropriate generic HRTF transfer functions which are not initially adapted to them.
- the second approach suggests learning by a computer of the reactions of a user participating in an interactive game or responding to an interactive questionnaire. The computer iteratively reconstructs the set of HRTF transfer functions suitable for the user from the observation of his localization performance and / or his responses.
- the present invention improves the situation.
- a first aspect of the invention relates to a method for processing individualized data representative of the directivity of an individualized audio system, according to claim 1.
- the successive decomposition in a first base of N independent components common to all the individuals of the first set, then in a second base of P independent components advantageously makes it possible to compress the stored data.
- the numbers N and P of independent components can be chosen as a function of criteria linked to the size of the data stored and to the precision desired for the filter sets.
- the second basis of P independent components can be a basis of spherical harmonics of order P and the second set of weighting coefficients is a set of spherical coefficients.
- the storage of the sets of filters in the form of morphological data advantageously makes it possible to easily apply transformations in order to adapt the second set of weighting coefficients of an individual from the initial set.
- the initial set can thus be used as a starting point for a quick and non-binding determination of sets of filters for users other than the users of the initial set.
- the transformation can comprise at least the application of a rotation matrix to the set of spherical coefficients associated with the selected individual.
- the method comprises the application of an inverse Fourier transform to the new set of filters prior to the temporal resampling.
- the morphological data relate at least to the auditory pinna of the user.
- the morphological data having the most influence on the filter set associated with an individual are taken into account when determining a new set for a new individual.
- the filters can be transfer functions in the frequency domain (or the modules of these transfer functions), each independent component can be a function having a non-zero spectrum in a frequency band. given, and the given frequency bands may be distinct.
- independent components can be expressed in logarithmic scale of frequencies.
- the modules of the set of filters can be deconvolved by a spatial average of the modules of the set of filters and the N independent components can be determined from the deconvolved modules.
- This embodiment makes it possible to reduce the variance of the filters by eliminating the part common to all the filters and makes it possible to work on real values rather than complex (DTF).
- a second aspect of the invention relates to a computer program product comprising program code instructions recorded on a medium readable by a computer, for the execution of the steps of the method according to the first aspect of the invention.
- a third aspect relates to a device for processing individualized data representative of the directivity of an audio system, according to claim 10.
- the figure 1 is a diagram illustrating the general steps of a data processing method according to one embodiment of the invention.
- a personalized set of filters is obtained.
- the initial set of individuals is a restricted set of individuals for which the solutions of the state of the art could be applied in order to obtain a set of filters personalized for each of the individuals.
- each individual was tested in an anechoic chamber in order to obtain at least one personalized set of filters.
- two sets of custom filters are obtained for each individual, one for each ear canal.
- the sets of filters of the initial set of individuals are stored in a step 102, for example in a memory of a device implementing the method according to the invention.
- Filter sets can be expressed as the coefficients of a matrix.
- HRTF transfer functions in the frequency domain is considered without limitation as sets of filters.
- N independent components common to the sets of filters obtained are determined.
- the decomposition into independent components disclosed in the document “Independent conduct analysis”, Stone JV, 2004, John Wiley & Sons can be applied to the modules of the filters of a set (HRTF transfer functions), the modules being optionally deconvolved (frequency division) by the spatial mean of the set of filters. Such an operation is equivalent to removing from the HRTF transfer functions the frequency components common to all the filters.
- Such deconvolved modules are called DTF hereafter. Modules can be optionally smoothed in order to keep only the perceptually relevant frequency variations.
- any HRTF (or DTF) transfer function modulus of the initial set of individuals can be reconstructed by a linear combination of independent components weighted by weighting coefficients, as shown in Figure figure 2 .
- a first matrix 200 of coefficients w i, j , i varying between 1 and M (2 * M being the total number of directions measured, M filters corresponding to one of the two ears of the listener) and j varying between 1 and N represents the weighting coefficients obtained after decomposition of the filters corresponding to one of the ears of a set on a basis formed of the N independent components.
- a second matrix 201 of coefficients c n, f , with n varying between 1 and N and f varying between 1 and F represents the coefficients of the N independent components, each row corresponding to one of the N independent components.
- a third matrix 202 represents a set of filters (the deconvolved modules of the HRTF transfer functions in the preceding example) for an individual, for an ear, obtained in step 101, and comprises coefficients d m, f , m varying between 1 and M and f varying between 1 and F.
- Each row m of the third matrix 202 represents a filter for a given direction of space, and each column corresponds to a frequency (or a band of frequencies more precisely), translating thus the spectrum of HRTF transfer functions.
- the HRTF transfer function modules can be in logarithmic or linear scale, abscissa or ordinate, which results in four distinct configurations (linear, linear), (logarithmic, linear), (linear, logarithmic) and (logarithmic, logarithmic).
- a logarithmic scale on the abscissa amounts to resampling the spectrum of a transfer function (a row of the matrix 202) with a logarithmic and non-linear frequency step, which more precisely reflects the perceptual functioning of the human ear. (more sensitive in high frequencies than low frequencies).
- a logarithmic scale on the ordinate amounts to considering 20 * log 10 (abs (HRTF)), abs (HRTF) representing the modules of the HRTF transfer functions.
- each row of the second matrix 201 represents an independent component, each coefficient of the row corresponding to the energy of the independent component in a given frequency band.
- the first matrix 200 depends on the azimuth and the elevation (on the ordinate) and on the weights assigned to each independent component (on the abscissa).
- the set of coefficients w m, n for a given column n represents, for an individual, the directivity for an independent component for the component n.
- Each index m corresponding to a measurement for a direction (azimuth (m), elevation (m)).
- the first matrix 200 is determined in a step 104, by decomposing each of the sets of filters obtained in step 101, into the base formed from the N independent components.
- the coefficients of a column of the first matrix 200 represent the values of the weights for an independent component for the different measurement directions. They thus represent a figure of spatial directivity.
- the figure 4 illustrates such figures of spatial directivity for eight individuals of the initial set of individuals, according to one embodiment of the invention. We see on the figure 4 that the spatial directivities look the same from one individual to another and that rotations can be applied to bring these spatial directivities closer together.
- the figure 4 presents in particular the weighting coefficients of the first matrix 200, for each individual, applied to the third independent component (third row of the second matrix 201) for eight different individuals. These are therefore the respective third columns of the first matrices 200 for the eight individuals.
- the columns are re-cut by the same elevation and represented in a three-dimensional way.
- the abscissa corresponds to the azimuth expressed in degrees, and the ordinate corresponds to the elevation in degrees.
- the third dimension is represented by color variations (in shades of gray on the figure 4 ).
- the shades of gray represent the values of the weighting coefficients.
- the figure 4 can thus be interpreted as a set of directivity figures for the third independent components of eight individuals of the initial set.
- each set of weighting coefficients (each first matrix 200 of an individual from the initial set ) in a base of P independent functions in the mathematical sense, for example in a base of spherical harmonics of order P-1, in order to obtain a set of spherical coefficients.
- the choice of the base of spherical harmonics allows the easy application of rotations to the sets of spherical coefficients in order to recalculate a new set of spherical coefficients following a rotation of the measurement reference frame, which is not the case with a basis of independent components in two dimensions.
- the determination of a set of spherical coefficients amounts to carrying out a spatial Fourier transform of the directivities (of a first matrix 200 therefore).
- each set of spherical coefficients obtained in association with an identifier of the individual to which it corresponds.
- the decomposition into spherical harmonics thus makes it possible to fully characterize a set of filters corresponding to the directivity of the ear canal of one of the individuals by means of spherical coefficients cw ic, p which are of dimension P * N, where P-1 is the order of the decomposition into spherical harmonics and N the number of independent components.
- N and P can thus be chosen as a function of a compromise between the level of compression and storage constraints, in order to ensure that the complexity of the HRTF transfer functions is reduced after successive decompositions.
- a second advantage arising from the successive application of a decomposition on a basis of N independent components then on a basis of spherical harmonics is linked to the customization of the transfer functions HRTF or DTF.
- the steps 101 to 106 detailed previously have been applied to an initial set of individuals, the set comprising a limited number of individuals (around fifty for example) due to the complexity linked to the acquisition of the functions of HRTF transfer to step 101.
- the sets of spherical coefficients determined for this restricted number of individuals can also be used to rapidly determine a set of filters for a new individual, not belonging to the initial set.
- the method according to the invention can comprise obtaining current morphological data of a new individual.
- a transformation which can include a simple rotation defined by three axes of rotation ( ⁇ , ⁇ , ⁇ ).
- a homothety To can be applied.
- the transformation parameters can be obtained by comparison between two three-dimensional meshes of two individuals, and more generally by comparison between data morphological data of the individuals of the initial set and the current morphological data of the new individual.
- the parameters ⁇ , ⁇ , ⁇ and ⁇ can also depend on a factor f representing a frequency band or a set of frequency bands.
- morphological data of the individuals of the first set can also be obtained in step 101 described above and then stored in step 102. These morphological data can describe the geometry of the linear system whose directivity is characterized by the set of associated filters.
- No restriction is attached to the means used to obtain the morphological data of the individuals of the initial set as well as the current morphological data.
- they can be obtained by direct measurements on the individual, from photographs or even using the three-dimensional scanner of the Kinect TM type for example.
- the morphological data related to the flag of the individual can be particularly taken into account in determining the transformation parameters. Indeed, the bell is the most influencing factor in the information of HRTF filter sets.
- the current morphological data is compared with the set of morphological data of the individuals of the initial set, with a view to selecting, at a step 109, an individual from the initial set. For example, the individual of the initial set having the parameters closest to the current parameters is selected.
- the morphological data to be stored and compared as being 3D meshes of the pavilions, one can search in the base for the 3D mesh which, after a rotation and a homothety, will be closest to the current 3D mesh. No restriction is attached to the criterion used to characterize the proximity of the morphological parameters.
- a transformation to be applied to the set of spherical coefficients associated with the selected individual is determined from the current morphological data.
- the transformation is determined by determining the first parameters that allow data to be passed current morphological data to the morphological data of the individual selected from the initial set. In the example above, the values of the rotation found in the previous step are used. From these first parameters, are deduced the transformation parameters making it possible to transform the set of filters of the selected individual into a new set of filters.
- such a method amounts to determining a transformation model and its parameters on the sets of filters characterizing the directivities of the systems from a signal point of view, another transformation model and its parameters describing the geometries, shapes or morphologies of the systems, and also to determine a function to match these two models.
- the transformation is then applied to the set of spherical coefficients associated with the selected individual in order to obtain a set of spherical coefficients transformed in a step 111.
- the transformed set of spherical coefficients is stored in association with an identifier of the new individual at a step 112.
- the figure 5 represents device 500 according to one embodiment of the invention.
- the device 500 comprises a random access memory 503 and a processor 502 for storing instructions allowing the implementation of steps 101 to 112 of the method described above with reference to figure 1 .
- the device also comprises a database 504 for storing data intended to be kept after the application of the method, in particular the sets of spherical coefficients, the independent components, and optionally the base of spherical harmonics.
- the device 500 further comprises an input interface 501 intended to receive the sets of filters of the initial set of individuals, and optionally the morphological parameters of the individuals of the initial set and the current morphological parameters.
- the device 500 further comprises an output interface 505 for the transmission of data resulting from the application of the method according to the invention. For example, the output interface can transmit the modified filter set or the transformed spherical coefficient set obtained for the new user.
- the present invention is not limited to the embodiments described above by way of examples; it extends to other variants, included within the scope of the protection defined by the following claims.
- the present invention makes it possible to improve the quality of immersive audio rendering in binaural systems, since it makes it possible to easily obtain a set of filters personalized for an individual from morphological data, without requiring long and expensive measurements on each of the individuals.
- the invention thus applies to communications services including audio conferencing and content distribution services or applications (music, films, games, user interfaces, etc.).
- the present invention allows the compression of the sets of filters (HRTF or DTF for example), which facilitates the storage, exchange or loading thereof.
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Description
La présente invention concerne le domaine de la restitution de données sonores.The present invention relates to the field of the restitution of sound data.
Elle trouve des applications, en particulier, mais non exclusivement, dans le cadre de services de télécommunication proposant une restitution spatialisée du son, comme par exemple dans le cas d'une audioconférence entre plusieurs locuteurs, d'une diffusion de bande annonce de cinéma ou d'une diffusion de tout type de contenu audio multicanal. L'invention s'applique également dans le cas de terminaux de télécommunication, notamment mobiles, pour lesquels il est envisagé un rendu sonore avec un système d'écoute stéréophonique (un casque par exemple) permettant à l'auditeur de positionner les sources sonores dans l'espace.It finds applications, in particular, but not exclusively, in the context of telecommunications services offering spatialized sound reproduction, such as for example in the case of an audioconference between several speakers, of a cinema trailer broadcast or broadcasting of any type of multichannel audio content. The invention also applies in the case of telecommunications terminals, in particular mobile, for which it is envisaged a sound reproduction with a stereophonic listening system (a headset for example) allowing the listener to position the sound sources in space.
A cet effet, l'invention exploite des systèmes linéaires invariants et stationnaires pouvant être caractérisés par un ensemble de filtres dépendant d'une direction entre la source sonore et l'un des conduits auditifs de l'auditeur.To this end, the invention uses invariant and stationary linear systems that can be characterized by a set of filters depending on a direction between the sound source and one of the listener's auditory canals.
Cet ensemble de filtres représente la directivité du système. Les filtres peuvent être représentés sous leur forme temporelle (sous forme de réponse impulsionnelle) ou fréquentielle (sous forme de fonction de transfert).This set of filters represents the directivity of the system. Filters can be represented in their time (as an impulse response) or frequency (as a transfer function) form.
A titre d'exemple, un individu ou une tête artificielle avec un microphone à l'entrée de chaque conduit auditif sont des cas particuliers d'un tel système linéaire invariant et stationnaire. Dans ce cas le système peut être caractérisé par ses fonctions de transfert, spécifiques à chaque individu.By way of example, an individual or an artificial head with a microphone at the entrance to each auditory canal are particular cases of such an invariant and stationary linear system. In this case, the system can be characterized by its transfer functions, specific to each individual.
Les fonctions de transfert définissent les caractéristiques spatiales d'audition de l'individu en prenant en compte notamment les réflexions liées à sa morphologie.The transfer functions define the spatial hearing characteristics of the individual by taking into account in particular the reflections linked to his morphology.
Les fonctions de transfert sont classiquement appelées fonctions de transfert de type HRTF pour « Head Related Transfer Function », quand les filtres sont donnés dans le domaine fréquentiel, et HRIR pour « Head Related Impulse Response », quand les filtres sont donnés dans le domaine temporel. Il est possible de passer d'une représentation à une autre par une transformée de Fourier.The transfer functions are classically called transfer functions of the HRTF type for “ Head Related Transfer Function ”, when the filters are given in the frequency domain, and HRIR for “ Head Related Impulse Response ”, when the filters are given in the time domain. . It is possible to go from one representation to another by a Fourier transform.
Les fonctions de transfert HRTF sont donc un ensemble de valeurs complexes. Il est possible de revenir à des valeurs réelles en prenant leurs modules respectifs : on obtient ainsi les modules des HRTF.HRTF transfer functions are therefore a set of complex values. It is possible to return to real values by taking their respective moduli: we thus obtain the moduli of the HRTF.
La division de chaque module par la moyenne spatiale des modules pour une fréquence donnée permet d'obtenir ce qui est communément nommé dans la littérature « Directional Transfer Function ». The division of each module by the spatial average of the modules for a given frequency makes it possible to obtain what is commonly called in the literature “ Directional Transfer Function”.
L'invention peut être généralisée à des directivités de systèmes présentant des formes et/ou des nombres de capteurs différents (par exemple un téléphone mobile avec 3 microphones). Sans nuire à la généralisation de l'invention à tout système linéaire pouvant être caractérisé par des ORTF, et afin de faciliter la compréhension de l'invention, il est considéré par la suite le cas particulier des fonctions de transfert DTF. En effet on peut passer des fonctions de transfert DTF aux fonctions de transfert HRTF en calculant des filtres à phase minimale associés aux fonctions de transfert DTF et en y ajoutant un retard modélisant les retards de propagations entre les capsules (retard inter-aural par un humain). La personnalisation de ces retards est obtenue par d'autres techniques bien connues et non décrites ici.The invention can be generalized to the directivities of systems having different shapes and / or numbers of sensors (for example a mobile telephone with 3 microphones). Without prejudicing the generalization of the invention to any linear system that can be characterized by ORTFs, and in order to facilitate understanding of the invention, the particular case of DTF transfer functions is considered hereinafter. In fact, it is possible to pass from the DTF transfer functions to the HRTF transfer functions by calculating minimum phase filters associated with the DTF transfer functions and by adding a delay to them modeling the propagation delays between the capsules (inter-aural delay by a human ). The personalization of these delays is obtained by other techniques well known and not described here.
Une technique utilisant des fonctions de transfert de type HRTF est la synthèse binaurale. Cette technique repose sur l'utilisation de filtres dits « binauraux », qui reproduisent les fonctions de transfert acoustiques entre la ou les sources sonores et les conduits auditifs de l'auditeur. Ces filtres servent à simuler des indices de localisation auditive qui permettent à un auditeur de localiser les sources sonores en situation d'écoute réelle.One technique using HRTF-type transfer functions is binaural synthesis. This technique is based on the use of so-called “binaural” filters, which reproduce the acoustic transfer functions between the sound source (s) and the auditory canals of the listener. These filters are used to simulate auditory localization cues that allow a listener to locate sound sources in a real listening situation.
Les techniques liées à la synthèse binaurale sont donc basées sur une paire de signaux binauraux qui alimente un système de restitution. Les deux signaux binauraux peuvent être obtenus par traitement du signal, en filtrant un signal monophonique par les filtres binauraux qui reproduisent les propriétés de la propagation acoustique entre la source placée à une position donnée et chacun des conduits auditifs de l'auditeur.The techniques linked to binaural synthesis are therefore based on a pair of binaural signals which feeds a reproduction system. The two binaural signals can be obtained by signal processing, by filtering a monophonic signal by binaural filters which reproduce the properties of the acoustic propagation between the source placed at a given position and each of the listener's ear canals.
La synthèse binaurale peut être utilisée pour différentes restitutions comme par exemple une restitution au moyen d'un casque avec deux oreillettes, ou au moyen de deux haut-parleurs. L'objectif est la reconstruction d'un champ sonore au niveau des oreilles de l'auditeur pratiquement identique à celui qu'auraient induit les sources réelles dans l'espace.Binaural synthesis can be used for different reproductions such as, for example, a reproduction by means of a headset with two earphones, or by means of two loudspeakers. The goal is reconstruction a sound field at the level of the listener's ears practically identical to that induced by real sources in space.
Les filtres binauraux prennent en compte l'ensemble des phénomènes acoustiques qui modifient les ondes acoustiques dans leur trajet entre la source et les conduits auditifs de l'auditeur. Les phénomènes acoustiques comprennent notamment la diffraction par la tête de l'auditeur et les réflexions sur le pavillon auditif et le haut du torse de l'utilisateur.Binaural filters take into account all the acoustic phenomena which modify the acoustic waves in their path between the source and the auditory canals of the listener. Acoustic phenomena include in particular diffraction from the listener's head and reflections on the auditory pinna and upper torso of the user.
Ces phénomènes acoustiques varient selon la position de la source sonore par rapport à l'auditeur et les variations permettent à l'auditeur de localiser la source dans l'espace. En effet, ces variations déterminent une forme de codage acoustique de la position de la source. Le système auditif d'un individu sait, par apprentissage, interpréter ce codage pour localiser la ou les sources sonores.These acoustic phenomena vary according to the position of the sound source relative to the listener and the variations allow the listener to locate the source in space. Indeed, these variations determine a form of acoustic coding of the position of the source. The hearing system of an individual knows, by learning, how to interpret this coding to locate the sound source (s).
Néanmoins, les phénomènes acoustiques de diffraction/réflexion dépendent fortement de la morphologie de l'auditeur. Une synthèse binaurale de qualité repose donc sur des filtres binauraux qui reproduisent au mieux le codage acoustique que produit naturellement le corps de l'auditeur, en prenant en compte les spécificités individuelles de sa morphologie.Nevertheless, the acoustic diffraction / reflection phenomena strongly depend on the morphology of the listener. A quality binaural synthesis therefore relies on binaural filters which best reproduce the acoustic coding that the listener's body naturally produces, taking into account the individual specificities of his morphology.
Lorsque ces conditions ne sont pas respectées, une dégradation des performances du rendu binaural est induite, ce qui se traduit notamment par une perception intracrânienne des sources et des confusions entre les localisations avant et arrière.When these conditions are not respected, a degradation in the performance of binaural rendering is induced, which is reflected in particular by an intracranial perception of the sources and confusion between the front and rear locations.
Ainsi, les filtres binauraux représentent les fonctions de transfert acoustiques ou fonctions de transfert de type HRTF qui modélisent les transformations engendrées par le torse, la tête et le pavillon de l'auditeur sur le signal acoustique provenant d'une source sonore. A chaque position de source sonore est associée une paire de fonctions HRTF, une pour chaque oreille. De plus, ces fonctions de transfert HRTF portent l'empreinte acoustique de la morphologie de l'individu sur lequel elles ont été mesurées.Thus, the binaural filters represent the acoustic transfer functions or HRTF type transfer functions which model the transformations generated by the listener's torso, head and pinna on the acoustic signal coming from a sound source. Each sound source position is associated with a pair of HRTF functions, one for each ear. In addition, these HRTF transfer functions carry the acoustic imprint of the morphology of the individual on which they were measured.
De manière bien connue, les fonctions de transfert HRTF sont obtenues au cours d'une phase de mesure. Une sélection de directions qui couvrent plus ou moins finement l'ensemble de l'espace entourant l'auditeur est fixée. Pour chaque direction, les fonctions de transfert HRTF gauche et droite sont mesurées au moyen de microphones insérés à l'entrée des conduits auditifs de l'auditeur. En générale, une sphère centrée sur l'auditeur est ainsi définie.In a well-known manner, the HRTF transfer functions are obtained during a measurement phase. A selection of directions which cover more or less finely the whole of the space surrounding the listener is fixed. For each direction, the left and right HRTF transfer functions are measured using microphones inserted at the entrance to the listener's ear canals. Usually, a listener-centered sphere is defined in this way.
Pour une mesure de bonne qualité, la mesure doit être réalisée dans une chambre anéchoïque, ou chambre sourde, de sorte que seules les réflexions et phénomènes acoustiques liés à l'auditeur soient pris en compte. Au final, si M directions sont mesurées, on obtient, pour un auditeur donné, une base de donnée de 2M fonctions de transfert de type HRTF (car deux canaux auditifs droit et gauche) représentant, pour chaque conduit auditif, chacune des positions des sources. Ces techniques nécessitent donc de réaliser les mesures sur l'auditeur directement. La durée d'une telle opération de mesure est très longue car il est nécessaire de mesurer un grand nombre de directions.For a good quality measurement, the measurement must be carried out in an anechoic chamber, or an anechoic chamber, so that only the reflections and acoustic phenomena linked to the listener are taken into account. In the end, if M directions are measured, we obtain, for a given listener, a database of 2M HRTF type transfer functions (because two right and left auditory channels) representing, for each auditory canal, each of the positions of the sources. . These techniques therefore require carrying out the measurements on the listener directly. The duration of such a measuring operation is very long because it is necessary to measure a large number of directions.
Certains individus passent ainsi de longues heures en laboratoire afin d'y faire analyser la signature acoustique associée à leur physionomie dans le détail, ainsi que leurs capacités de perception de l'espace sonore en trois dimensions. Ces individus bénéficient ensuite d'une écoute binaurale façonnée à partir des résultats d'analyse, offrant un confort et une impression sonore de grande qualité.Some individuals thus spend long hours in the laboratory in order to have the acoustic signature associated with their physiognomy analyzed in detail, as well as their ability to perceive sound space in three dimensions. These individuals then benefit from binaural listening shaped from the analysis results, offering comfort and a high quality sound impression.
Afin de faire profiter de cette qualité et de ce confort à un ensemble plus large d'auditeurs, notamment dans le cadre de services destinés au grand public, il est nécessaire de disposer de filtres personnalisés à chacun des auditeurs.In order to provide this quality and comfort to a wider set of listeners, particularly in the context of services intended for the general public, it is necessary to have personalized filters for each of the listeners.
Il est toutefois difficilement concevable de mesurer l'ensemble des clients d'un service dans des chambres sourdes (qui sont rares et coûteuses). De plus, la durée et la pénibilité des mesures sont difficilement supportables pour le grand public.However, it is hardly conceivable to measure all the customers of a service in deaf rooms (which are rare and expensive). In addition, the duration and arduousness of the measures are difficult to bear for the general public.
Il est ainsi souhaitable de disposer de solutions permettant d'obtenir les signatures acoustiques d'individus de manière rapide, fiable et peu intrusive afin de pouvoir généraliser les résultats obtenus en chambre anéchoïque sur un petit nombre de sujets, à une population très importante.It is thus desirable to have solutions making it possible to obtain the acoustic signatures of individuals in a rapid, reliable and not very intrusive manner in order to be able to generalize the results obtained in an anechoic chamber on a small number of subjects, to a very large population.
Une solution pratique commençant à émerger consiste à proposer à l'utilisateur de mesurer ses propres fonctions de transfert HRTF dans son lieu habituel d'écoute afin d'émuler sur un casque sonore son expérience d'écoute en studio ou dans son salon. Les inconvénients liés à ce type de solutions sont liés au fait de ne mesurer qu'un faible nombre de positions fixes et de rendre difficile la séparation entre l'information liée au dispositif de diffusion proprement dit et le lieu d'écoute. Différentes études ont été consacrées à l'élaboration de méthodes permettant de réduire certaines contraintes pratiques comme la mesure dynamique (
Différentes pistes proposant des solutions alternatives sont explorées. Une première piste consiste à calculer les filtres à partir de l'acquisition de la morphologie de l'auditeur et notamment de son pavillon. I Wen Zhang et al. proposent ainsi de décomposer une fonction de transfert HRTF sur une base de fonction indépendantes ("
La transformation des fonctions de transfert HRTF pour les adapter à un individu donné est alors pilotée par la comparaison des morphologies du pavillon origine issu de la base de données et du pavillon cible de l'individu donné. Cette comparaison repose sur une technique d'appariement des maillages tridimensionnels des pavillons. Une autre méthode consiste à utiliser des paramètres morphologiques pour créer ou déformer un maillage tridimensionnel, qui sera ensuite utilisé pour un calcul détaillé et une simulation numérique des fonctions de transfert HRTF de l'individu, par éléments finis de frontière par exemple. Il est également possible, à partir des paramètres morphologiques d'un individu donné, de rechercher dans une base de données un individu tiers possédant des paramètres morphologiques proches.The transformation of the HRTF transfer functions to adapt them to a given individual is then controlled by the comparison of the morphologies of the original flag from the database and the target flag of the given individual. This comparison is based on a technique of matching the three-dimensional meshes of the pavilions. Another method consists in using morphological parameters to create or deform a three-dimensional mesh, which will then be used for a detailed calculation and a numerical simulation of the HRTF transfer functions of the individual, by finite elements of border for example. It is also possible, from the morphological parameters of a given individual, to search in a database a third individual with similar morphological parameters.
Certains travaux proposent d'exploiter en entrée un maillage tridimensionnel de la morphologie du sujet et plus particulièrement de son pavillon, et d'autres des mesures de paramètres morphologiques des utilisateurs. Une méthode pour acquérir la morphologie du pavillon consiste à utiliser un scan tridimensionnel, mais cette méthode est parfois problématique dans la mesure où elle nécessite à la fois un matériel et une mise en œuvre spécifiques.Some works propose to use as input a three-dimensional mesh of the morphology of the subject and more particularly of his pinna, and others of the measurements of morphological parameters of the users. One method of acquiring pinna morphology is to use a three-dimensional scan, but this method is sometimes problematic as it requires both specific hardware and implementation.
Des solutions alternatives sont mises au point soit en dérivant des scans tridimensionnels à partir d'un jeu de photographies (
D'autres travaux tentent de mettre en place des méthodes d'apprentissage qui regroupent deux approches opposées.Other works attempt to set up learning methods that combine two opposing approaches.
La première approche consiste à étudier la capacité des auditeurs à s'approprier des fonctions de transfert HRTF génériques et qui ne leur sont pas adaptées au départ. La deuxième approche, au contraire, suggère un apprentissage par un ordinateur des réactions d'un utilisateur participant à un jeu interactif ou répondant à un questionnaire interactif. L'ordinateur reconstitue de manière itérative le jeu de fonctions de transfert HRTF qui convient à l'utilisateur à partir de l'observation de ses performances de localisation et/ou de ses réponses.The first approach consists in studying the capacity of the auditors to appropriate generic HRTF transfer functions which are not initially adapted to them. The second approach, on the contrary, suggests learning by a computer of the reactions of a user participating in an interactive game or responding to an interactive questionnaire. The computer iteratively reconstructs the set of HRTF transfer functions suitable for the user from the observation of his localization performance and / or his responses.
Toutefois, le stockage des jeux de fonctions de transfert, leur transmission et leur chargement sont compliqués du fait de la taille des données représentant chaque jeu de fonctions de transfert.However, storing the sets of transfer functions, transmitting and loading them is complicated due to the size of the data representing each set of transfer functions.
De plus, les solutions nécessaires à la personnalisation d'un jeu de fonction de transfert, pour l'adapter à un auditeur donné, autres que les mesures en chambre sourde n'existent pas encore. Or comme expliqué ci-avant, les mesures en chambres sourdes sont complexes et coûteuses en ressources matérielles et logicielles ainsi qu'en temps, et ne sont ainsi pas transposables sur une grande population.In addition, the solutions necessary for the personalization of a set of transfer functions, to adapt it to a given listener, other than the measurements in an anechoic room do not yet exist. However, as explained above, measurements in anechoic rooms are complex and costly in terms of hardware and software resources as well as time, and are therefore not transposable to a large population.
La présente invention vient améliorer la situation.The present invention improves the situation.
A cet effet, un premier aspect de l'invention concerne un procédé de traitement de données individualisées et représentatives de la directivité d'un système audio individualisé, selon la revendication 1.To this end, a first aspect of the invention relates to a method for processing individualized data representative of the directivity of an individualized audio system, according to
La décomposition successive dans une première base de N composantes indépendantes commune à tous les individus du premier ensemble, puis dans une deuxième base de P composantes indépendantes permet avantageusement de compresser les données stockées. A cet effet, les nombres N et P de composantes indépendantes peuvent être choisis en fonction de critères liés à la taille des données stockées et à la précision souhaitée pour les jeux de filtre. La deuxième base de P composantes indépendantes peut être une base d'harmoniques sphériques d'ordre P et le deuxième jeu de coefficients de pondération est un jeu de coefficients sphériques.The successive decomposition in a first base of N independent components common to all the individuals of the first set, then in a second base of P independent components advantageously makes it possible to compress the stored data. To this end, the numbers N and P of independent components can be chosen as a function of criteria linked to the size of the data stored and to the precision desired for the filter sets. The second basis of P independent components can be a basis of spherical harmonics of order P and the second set of weighting coefficients is a set of spherical coefficients.
La décomposition dans une base d'harmoniques sphériques permet avantageusement de disposer de jeux de coefficients sphériques aisément transformables par application transformations comportant une rotation. Chaque individu de l'ensemble initial d'individus est en outre associé à un ensemble de données morphologiques, et le procédé comprend en outre les étapes suivantes :
- obtention de données morphologiques courantes d'un nouvel individu ;
- sélection d'un individu parmi l'ensemble initial par comparaison entre les données morphologiques courantes et les ensembles de données morphologiques des individus de l'ensemble initial ;
- application d'une transformation au deuxième jeu de coefficients de pondération associé à l'individu sélectionné en vue d'obtenir un deuxième jeu de coefficients de pondération transformé, la transformation étant déterminée à partir des données morphologiques courantes ;
- stockage du deuxième jeu de coefficients de pondération transformé en association avec un identifiant du nouvel individu.
- obtaining current morphological data of a new individual;
- selecting an individual from the initial set by comparison between the current morphological data and the morphological data sets of the individuals of the initial set;
- applying a transformation to the second set of weighting coefficients associated with the selected individual in order to obtain a second set of transformed weighting coefficients, the transformation being determined from current morphological data;
- storing the second set of weighting coefficients transformed in association with an identifier of the new individual.
Le stockage des jeux de filtres sous la forme de données morphologiques permet avantageusement d'appliquer de manière aisée des transformations afin d'adapter le deuxième jeu de coefficients de pondération d'un individu de l'ensemble initial. L'ensemble initial peut ainsi être utilisé comme point de départ pour une détermination rapide et non contraignante de jeux de filtres pour des utilisateurs autres que les utilisateurs de l'ensemble initial.The storage of the sets of filters in the form of morphological data advantageously makes it possible to easily apply transformations in order to adapt the second set of weighting coefficients of an individual from the initial set. The initial set can thus be used as a starting point for a quick and non-binding determination of sets of filters for users other than the users of the initial set.
En complément, la transformation peut comprendre au moins l'application d'une matrice de rotation au jeu de coefficients sphériques associé à l'individu sélectionné.In addition, the transformation can comprise at least the application of a rotation matrix to the set of spherical coefficients associated with the selected individual.
L'application d'une matrice de rotation à un jeu de coefficients dans une base de coordonnées sphériques permet d'appliquer aisément une rotation aux directivités des jeux de filtres représentés, et permettent ainsi d'adapter facilement les jeux de filtres des individus de l'ensemble initial.The application of a rotation matrix to a set of coefficients in a base of spherical coordinates makes it possible to easily apply a rotation to the directivities of the sets of filters represented, and thus makes it possible to easily adapt the sets of filters of the individuals of the 'initial set.
En complément, le procédé peut comprendre en outre les étapes suivantes :
- application d'une homothétie aux N composantes indépendantes, l'homothétie étant déterminée à partir des données morphologiques courantes, afin d'obtenir N composantes indépendantes transformées ;
- multiplication du jeu de coefficients sphériques transformé par une matrice formée par les N composantes indépendantes transformées, en vue d'obtenir un jeu de filtres modifié en association avec l'identifiant du nouvel individu.
- application of a homothety to the N independent components, the homothety being determined from current morphological data, in order to obtain N transformed independent components;
- multiplication of the set of spherical coefficients transformed by a matrix formed by the N transformed independent components, with a view to obtaining a set of filters modified in association with the identifier of the new individual.
En variante, le procédé peut comprendre en outre les étapes suivantes :
- multiplication du jeu de coefficients sphériques transformé par une matrice formée par les N composantes indépendantes, en vue d'obtenir un nouveau jeu de filtres ;
- application d'une homothétie par ré-échantillonnage temporel du nouveau jeu de filtres en vue d'obtenir un jeu de filtres modifié en association avec l'identifiant du nouvel individu.
- multiplication of the set of spherical coefficients transformed by a matrix formed by the N independent components, with a view to obtaining a new set of filters;
- application of a scaling by temporal resampling of the new set of filters with a view to obtaining a set of filters modified in association with the identifier of the new individual.
En complément, lorsque le nouveau jeu de filtres est dans le domaine fréquentiel, le procédé comprend l'application d'une transformée de Fourier inverse au nouveau jeu de filtres préalablement au ré-échantillonnage temporel.In addition, when the new set of filters is in the frequency domain, the method comprises the application of an inverse Fourier transform to the new set of filters prior to the temporal resampling.
Selon un mode de réalisation, les données morphologiques sont relatives au moins au pavillon auditif de l'utilisateur.According to one embodiment, the morphological data relate at least to the auditory pinna of the user.
Ainsi, les données morphologiques ayant le plus d'influence sur le jeu de filtre associé à un individu, sont prises en compte lors de la détermination d'un nouveau jeu pour un nouvel individu.Thus, the morphological data having the most influence on the filter set associated with an individual are taken into account when determining a new set for a new individual.
Selon des modes de réalisation de l'invention, les filtres peuvent être des fonctions de transfert dans le domaine fréquentiel (ou les modules de ces fonctions de transferts), chaque composante indépendante peut être une fonction ayant un spectre non nul dans une bande de fréquence donnée, et les bandes de fréquences données peuvent être distinctes.According to embodiments of the invention, the filters can be transfer functions in the frequency domain (or the modules of these transfer functions), each independent component can be a function having a non-zero spectrum in a frequency band. given, and the given frequency bands may be distinct.
En complément, les composantes indépendantes peuvent être exprimées en échelle logarithmique de fréquences.In addition, the independent components can be expressed in logarithmic scale of frequencies.
L'utilisation d'une échelle logarithmique permet de traduire de manière plus précise le fonctionnement perceptif de l'oreille humaine (plus sensible dans les hautes fréquences que les basses fréquences).The use of a logarithmic scale makes it possible to translate more precisely the perceptual functioning of the human ear (more sensitive in the high frequencies than the low frequencies).
Selon un mode de réalisation, pour chaque jeu de filtres obtenu, les modules du jeu de filtres peuvent être déconvolués par une moyenne spatiale des modules du jeu de filtres et les N composantes indépendantes peuvent être déterminées à partir des modules déconvolués.According to one embodiment, for each set of filters obtained, the modules of the set of filters can be deconvolved by a spatial average of the modules of the set of filters and the N independent components can be determined from the deconvolved modules.
Ce mode de réalisation permet de réduire la variance des filtres en éliminant la partie commune à tous les filtres et permet de travailler sur des valeurs réelles plutôt que complexes (DTF).This embodiment makes it possible to reduce the variance of the filters by eliminating the part common to all the filters and makes it possible to work on real values rather than complex (DTF).
Un deuxième aspect de l'invention concerne un produit programme d'ordinateur comprenant des instructions de code de programme enregistrées sur un support lisible par un ordinateur, pour l'exécution des étapes du procédé selon le premier aspect de l'invention.A second aspect of the invention relates to a computer program product comprising program code instructions recorded on a medium readable by a computer, for the execution of the steps of the method according to the first aspect of the invention.
Un troisième aspect concerne un dispositif de traitement de données individualisées et représentatives de la directivité d'un système audio, selon la revendication 10.A third aspect relates to a device for processing individualized data representative of the directivity of an audio system, according to
D'autres caractéristiques et avantages de l'invention apparaîtront à l'examen de la description détaillée ci-après, et des dessins annexés sur lesquels:
- la
figure 1 est un diagramme représentant les étapes d'un procédé de traitement de données selon un mode de réalisation de l'invention; - la
figure 2 représente une décomposition d'un jeu de filtres dans une base de composantes indépendantes selon un mode de réalisation de l'invention; - la
figure 3 représente des composantes indépendantes obtenues à partir d'un ensemble initial de jeux de filtres selon un mode de réalisation de l'invention ; - la
figure 4 illustre des figures de directivité pour une même composante indépendante pour huit individus distincts, selon un mode de réalisation de l'invention ; - la
figure 5 illustre un dispositif selon un mode de réalisation de l'invention.
- the
figure 1 is a diagram representing the stages of a data processing method according to one embodiment of the invention; - the
figure 2 represents a decomposition of a set of filters in a base of independent components according to one embodiment of the invention; - the
figure 3 represents independent components obtained from an initial set of sets of filters according to one embodiment of the invention; - the
figure 4 illustrates directivity figures for the same independent component for eight distinct individuals, according to one embodiment of the invention; - the
figure 5 illustrates a device according to an embodiment of the invention.
La
A une étape 101, pour chaque individu d'un ensemble initial d'individus, un jeu de filtres personnalisé est obtenu. L'ensemble initial d'individus est un ensemble restreint d'individus pour lesquels les solutions de l'état de la technique ont pu être appliqués afin d'obtenir un jeu de filtres personnalisé pour chacun des individus.In a
Par exemple, chaque individu a fait l'objet de tests en chambre anéchoïque afin d'obtenir au moins un jeu de filtres personnalisé. Généralement, deux jeux de filtres personnalisés sont obtenus pour chaque individu, un pour chaque conduit auditif.For example, each individual was tested in an anechoic chamber in order to obtain at least one personalized set of filters. Typically, two sets of custom filters are obtained for each individual, one for each ear canal.
Aucune restriction n'est cependant attachée à la manière dont ont été acquis les jeux de filtres à l'étape 101. Les jeux de filtres de l'ensemble initial d'individus sont stockés à une étape 102, par exemple dans une mémoire d'un dispositif mettant en œuvre le procédé selon l'invention.No restriction is however attached to the way in which the sets of filters were acquired in
Les jeux de filtres peuvent être exprimés sous la forme de coefficients d'une matrice. Comme détaillé précédemment, l'exemple de fonctions de transfert HRTF dans le domaine fréquentiel est considéré de manière non restrictive en tant que jeux de filtres.Filter sets can be expressed as the coefficients of a matrix. As detailed previously, the example of HRTF transfer functions in the frequency domain is considered without limitation as sets of filters.
A une étape 103, N composantes indépendantes communes aux jeux de filtres obtenus sont déterminées. Par exemple, la décomposition en composantes indépendantes divulguée dans le document
Ainsi, n'importe quel module de fonction de transfert HRTF (ou DTF) de l'ensemble initial d'individus peut être reconstruit par une combinaison linéaire de composantes indépendantes pondérées par des coefficients de pondération, tel qu'illustré sur la
Une première matrice 200 de coefficients wi,j, i variant entre 1 et M ( 2*M étant le nombre total de directions mesurées, M filtres correspondant à une des deux oreilles de l'auditeur) et j variant entre 1 et N représente les coefficients de pondération obtenus après décomposition des filtres correspondant à l'une des oreilles d'un jeu sur une base formée des N composantes indépendantes.A
Une deuxième matrice 201 de coefficients cn,f, avec n variant entre 1 et N et f variant entre 1 et F représente les coefficients des N composantes indépendantes, chaque ligne correspondant à l'une des N composantes indépendantes.A
Une troisième matrice 202 représente un jeu de filtres (les modules déconvolués des fonctions de transfert HRTF dans l'exemple précédent) pour un individu, pour une oreille, obtenu à l'étape 101, et comprend des coefficients dm,f, m variant entre 1 et M et f variant entre 1 et F. Chaque ligne m de la troisième matrice 202 représente un filtre pour une direction de l'espace donnée, et chaque colonne correspond à une fréquence (ou une bande de fréquences plus précisément), traduisant ainsi le spectre des fonctions de transfert HRTF. Les modules des fonctions de transfert HRTF peuvent être en échelle logarithmique ou linéaire, en abscisse ou en ordonnée, ce qui résulte en quatre configurations distinctes (linéaire, linéaire), (logarithmique, linéaire), (linéaire, logarithmique) et (logarithmique, logarithmique). Une échelle logarithmique en abscisse revient à ré-échantillonner le spectre d'une fonction de transfert (une ligne de la matrice 202) avec un pas fréquentiel logarithmique et non linéaire, ce qui traduit de manière plus précise le fonctionnement perceptif de l'oreille humaine (plus sensible dans les hautes fréquences que les basses fréquences). Une échelle logarithmique en ordonnée revient à considérer 20*log10(abs(HRTF)), abs(HRTF) représentant les modules des fonctions de transfert HRTF.A
Comme indiqué ci-dessus, chaque ligne de la deuxième matrice 201 représente une composante indépendante, chaque coefficient de la ligne correspondant à l'énergie de la composante indépendante dans une bande de fréquences donnée.As indicated above, each row of the
La
La première matrice 200 dépend de l'azimut et de l'élévation (en ordonnée) et des poids affectés à chaque composante indépendante (en abscisse). L'ensemble des coefficients wm,n pour une colonne n donnée, représente, pour un individu, la directivité pour une composante indépendante pour la composante n. Chaque indice m correspondant à une mesure pour une direction (azimut (m), élévation(m)). La première matrice 200 est déterminée à une étape 104, par décomposition de chacun des jeux de filtres obtenus à l'étape 101, dans la base constituée à partir des N composantes indépendantes. Les coefficients d'une colonne de la première matrice 200 représentent les valeurs des pondérations pour une composante indépendante pour les différentes directions de mesures. Elles représentent ainsi une figure de directivité spatiale.The
La
La
Afin de rechercher de telles rotations et de diminuer encore la quantité d'informations décrivant un individu, l'invention prévoit de décomposer à une étape 105, chaque jeu de coefficients de pondération (chaque première matrice 200 d'un individu de l'ensemble initial) dans une base de P fonctions indépendantes au sens mathématique, par exemple dans une base d'harmoniques sphériques d'ordre P-1, afin d'obtenir un jeu de coefficients sphériques. Le choix de la base d'harmoniques sphériques permet l'application aisée de rotations aux jeux de coefficients sphériques afin de recalculer un nouveau jeu de coefficients sphériques suite à une rotation du référentiel de mesure, ce qui n'est pas le cas d'une base de composantes indépendantes en deux dimensions.In order to search for such rotations and to further reduce the quantity of information describing an individual, the invention provides for breaking down in a
La détermination d'un jeu de coefficients sphériques revient à réaliser une transformée de Fourier Spatiale des directivités (d'une première matrice 200 donc). La décomposition des directivités cwic,p pour la composante indépendante ic à l'ordre P en harmoniques sphériques s'exprime de la manière suivante :
A partir de chaque jeu de filtres d'un individu de l'ensemble initial, on obtient ainsi un jeu de coefficients sphériques. A une étape 106, chaque jeu de coefficients sphériques obtenu en association avec un identifiant d'individu auquel il correspond.From each set of filters of an individual of the initial set, we thus obtain a set of spherical coefficients. In a
La décomposition en harmoniques sphériques permet ainsi de caractériser entièrement un jeu de filtres correspondant à la directivité du conduit auditif de l'un des individus au moyen de des coefficients sphériques cwic,p qui sont de dimension P*N, où P-1 est l'ordre de la décomposition en harmoniques sphériques et N le nombre de composantes indépendantes.The decomposition into spherical harmonics thus makes it possible to fully characterize a set of filters corresponding to the directivity of the ear canal of one of the individuals by means of spherical coefficients cw ic, p which are of dimension P * N, where P-1 is the order of the decomposition into spherical harmonics and N the number of independent components.
La base d'harmoniques sphériques et les N composantes indépendantes sont communes à tous les individus, et donc à tous les jeux de filtres HRTF ou de DTF.The basis of spherical harmonics and the N independent components are common to all individuals, and therefore to all HRTF or DTF filter sets.
L'application successive d'une décomposition sur une base de N composantes indépendantes puis sur une base d'harmoniques sphériques permet un premier avantage qui est de réduire la quantité d'informations à analyser et permet de compresser les jeux de filtres HRTF.The successive application of a decomposition on a basis of N independent components then on a basis of spherical harmonics allows a first advantage which is to reduce the quantity of information to be analyzed and makes it possible to compress the HRTF filter sets.
A titre d'exemple, les solutions actuelles prévoient l'acquisition de jeux de filtres HRTF comprenant 1680 directions, pour deux oreilles d'un individu, pour une taille de filtre de 512 points à 48 kHz de fréquence d'échantillonnage, soit 1680*2*512=1720320 valeurs flottantes.By way of example, current solutions provide for the acquisition of HRTF filter sets comprising 1680 directions, for two ears of an individual, for a filter size of 512 points at 48 kHz sampling frequency, i.e. 1680 * 2 * 512 = 1720320 floats.
Une décomposition sur N=64 composantes indépendantes, puis sur une base d'harmoniques sphériques d'ordre 20 permet une reconstruction quasi parfaite en stockant uniquement 2*64*(20+1)=2688, soit un facteur de compression de 640. Il convient également de stocker les 64 composantes indépendantes (64*512=32768). Quant aux valeurs de la base d'harmoniques sphériques, elles peuvent être calculées ou stockées dans des tables. Ces dernières et les N composantes indépendantes sont communes à tous les jeux de filtres des individus.A decomposition on N = 64 independent components, then on a basis of spherical harmonics of
Les valeurs N et P peuvent ainsi être choisies en fonction d'un compromis entre le niveau de compression et des contraintes de stockage, et ce afin d'assurer que la complexité des fonctions de transfert HRTF est réduite après décompositions successives.The values N and P can thus be chosen as a function of a compromise between the level of compression and storage constraints, in order to ensure that the complexity of the HRTF transfer functions is reduced after successive decompositions.
Un deuxième avantage découlant de l'application successive d'une décomposition sur une base de N composantes indépendantes puis sur une base d'harmoniques sphériques est lié à la personnalisation des fonctions de transfert HRTF ou DTF. En effet, les étapes 101 à 106 détaillées précédemment ont été appliquées à un ensemble initial d'individus, l'ensemble comprenant un nombre restreint d'individus (une cinquantaine par exemple) du fait de la complexité liée à l'acquisition des fonctions de transfert HRTF à l'étape 101. Or, les jeux de coefficients sphériques déterminés pour ce nombre restreint d'individus peuvent également être utilisés pour déterminer rapidement un jeu de filtres pour un nouvel individu, n'appartenant pas à l'ensemble initial. L'avantage de la décomposition sur une base d'harmoniques sphériques est que, pour réaliser une rotation de l'ensemble d'un jeu de filtres HRTF ou DTF (rotation du référentiel de mesure), il suffit d'appliquer une matrice de rotation à au jeu de coefficients sphériques cw correspondant (voir à cet effet la thèse
A cet effet, à une étape 107, le procédé selon l'invention peut comprendre l'obtention de données morphologiques courantes d'un nouvel individu. En effet, il est possible de passer d'une morphologie d'un individu à une morphologie d'un nouvel individu en appliquant une transformation pouvant comprendre une simple rotation définie par trois axes de rotation (θ,ϕ,ρ). En outre une homothétie À peut être appliquée. Les paramètres de transformation peuvent être obtenus par comparaison entre deux maillages tridimensionnels de deux individus, et plus généralement par comparaison entre des données morphologiques des individus de l'ensemble initial et les données morphologiques courantes du nouvel individu.To this end, in a
Les paramètres θ,ϕ,ρ et λ peuvent en outre dépendre d'un facteur f représentant une bande de fréquences ou un ensemble de bandes de fréquences.The parameters θ, ϕ, ρ and λ can also depend on a factor f representing a frequency band or a set of frequency bands.
A cet effet, des données morphologiques des individus du premier ensemble peuvent également être obtenus à l'étape 101 précédemment décrite puis stockés à l'étape 102. Ces données morphologiques peuvent décrire la géométrie du système linéaire dont la directivité est caractérisée par le jeu de filtres associé.To this end, morphological data of the individuals of the first set can also be obtained in
Aucune restriction n'est attachée aux moyens utilisés pour obtenir les données morphologiques des individus de l'ensemble initial ainsi que les données morphologiques courantes. Par exemple, elles peuvent être obtenues par des mesures directes sur l'individu, à partir de photographies ou encore à l'aide du scanner tridimensionnel de type Kinect™ par exemple. Les données morphologiques liées au pavillon de l'individu peuvent particulièrement être pris en compte dans la détermination des paramètres de transformation. En effet, le pavillon est le facteur le plus influençant dans l'information des jeux de filtres HRTF.No restriction is attached to the means used to obtain the morphological data of the individuals of the initial set as well as the current morphological data. For example, they can be obtained by direct measurements on the individual, from photographs or even using the three-dimensional scanner of the Kinect ™ type for example. The morphological data related to the flag of the individual can be particularly taken into account in determining the transformation parameters. Indeed, the bell is the most influencing factor in the information of HRTF filter sets.
Ainsi, à une étape 108, les données morphologiques courantes sont comparées avec l'ensemble des données morphologiques des individus de l'ensemble initial, en vue de sélectionner, à une étape 109, un individu parmi l'ensemble initial. Par exemple, l'individu de l'ensemble initial ayant les paramètres les plus proches des paramètres courants est sélectionné. A titre d'exemple en considérant les données morphologiques à stocker et comparer comme étant des maillages 3D des pavillons, on peut rechercher dans la base le maillage 3D qui, après une rotation et une homothétie, sera le plus proche du maillage 3D courant. Aucune restriction n'est attachée au critère utilisé pour caractériser la proximité des paramètres morphologiques.Thus, at a
A une étape 110, une transformation à appliquer au jeu de coefficients sphériques associé à l'individu sélectionné est déterminée à partir des données morphologiques courantes. La transformation est déterminée en déterminant des premiers paramètres qui permettent de passer des données morphologiques courantes aux données morphologiques de l'individu sélectionné de l'ensemble initial. Dans l'exemple ci-dessus, les valeurs de la rotation trouvée à l'étape précédente sont utilisées. A partir de ces premiers paramètres, sont déduits les paramètres de transformation permettant de transformer le jeu de filtres de l'individu sélectionné en un nouveau jeu de filtres.In a
De manière générale, une telle méthode revient à déterminer un modèle de transformation et ses paramètres sur les jeux de filtres caractérisant les directivités des systèmes d'un point de vue signal, un autre modèle de transformation et ses paramètres décrivant, les géométries, formes ou morphologies des systèmes, et également de déterminer une fonction pour faire correspondre ces deux modèles.In general, such a method amounts to determining a transformation model and its parameters on the sets of filters characterizing the directivities of the systems from a signal point of view, another transformation model and its parameters describing the geometries, shapes or morphologies of the systems, and also to determine a function to match these two models.
La transformation est ensuite appliquée au jeu de coefficients sphériques associé à l'individu sélectionné afin d'obtenir un jeu de coefficients sphériques transformé à une étape 111.The transformation is then applied to the set of spherical coefficients associated with the selected individual in order to obtain a set of spherical coefficients transformed in a
Le jeu de coefficients sphériques transformé est stocké en association avec un identifiant du nouvel individu à une étape 112.The transformed set of spherical coefficients is stored in association with an identifier of the new individual at a
En outre, l'homothétie λ peut être appliquée de différentes manières :
- dilatation fréquentielle des N composantes indépendantes de la deuxième matrice 201 d'un facteur À, puis application de la multiplication matricielle de la
figure 2 pour obtenir un nouveau jeu de filtres HRTF ou DTF. Dans ce calcul, la première matrice 200 est obtenue à partir du jeu de coefficients sphériques transformé ; - application de la multiplication matricielle de la
figure 2 , la première matrice 200 étant obtenue à partir du jeu de coefficients sphériques transformé, puis application d'une transformée de Fourier inverse pour revenir dans le domaine temporel, et application de l'homothétie λ par un ré-échantillonnage temporel. La transformée de Fourier inverse est ainsi appliquée dans l'exemple particulier des jeux de filtres HRTF ou DTF. Toutefois, elle n'est pas nécessaire dans le cas où l'invention est appliquée à des jeux de filtres dans le domaine temporel.
- frequency expansion of the N independent components of the
second matrix 201 by a factor λ, then application of the matrix multiplication of thefigure 2 to get a new set of HRTF or DTF filters. In this calculation, thefirst matrix 200 is obtained from the transformed set of spherical coefficients; - application of the matrix multiplication of the
figure 2 , thefirst matrix 200 being obtained from the set of transformed spherical coefficients, then application of an inverse Fourier transform to return to the time domain, and application of the homothety λ by time resampling. The inverse Fourier transform is thus applied in the particular example of the HRTF or DTF filter sets. However, it is not necessary in the case where the invention is applied to sets of filters in the time domain.
La
Le dispositif 500 comprend une mémoire vive 503 et un processeur 502 pour stocker des instructions permettant la mise en œuvre des étapes 101 à 112 du procédé décrit ci-avant en référence à la
La présente invention ne se limite pas aux formes de réalisation décrites ci-avant à titre d'exemples ; elle s'étend à d'autres variantes, comprises dans l'étendue de la protection définie par les revendications qui suivent. Ainsi, la présente invention permet d'améliorer la qualité de rendu immersive audio dans les systèmes binauraux, puisqu'elle permet d'obtenir aisément un jeu de filtres personnalisé pour un individu à partir de données morphologiques, sans requérir de mesures longues et coûteuses sur chacun des individus. L'invention s'applique ainsi aux services de communications dont l'audioconférence et les services ou applications de diffusion de contenus (musique, films, jeux, interfaces utilisateur, etc). En outre, la présente invention permet la compression des jeux de filtres (HRTF ou DTF par exemple), ce qui facilite le stockage, l'échange ou le chargement de ceux-ci.The present invention is not limited to the embodiments described above by way of examples; it extends to other variants, included within the scope of the protection defined by the following claims. Thus, the present invention makes it possible to improve the quality of immersive audio rendering in binaural systems, since it makes it possible to easily obtain a set of filters personalized for an individual from morphological data, without requiring long and expensive measurements on each of the individuals. The invention thus applies to communications services including audio conferencing and content distribution services or applications (music, films, games, user interfaces, etc.). In addition, the present invention allows the compression of the sets of filters (HRTF or DTF for example), which facilitates the storage, exchange or loading thereof.
Claims (10)
- Method for processing individualized data representative of the directivity of an individualized audio system, said method comprising the following steps:- obtaining (101), for each individual of an initial set of individuals, at least one personalized set of binaural filters;- determining (103) N independent components common to the sets of filters obtained;- decomposing (104) each of the sets obtained into a first base formed from the N independent components with a view to obtaining, for each set of filters, a first set of weighting coefficients;- decomposing (105) each first set of weighting coefficients into a second base of P independent components, in order to obtain a second set of weighting coefficients, the second base of P independent components being a base of spherical harmonics of order P-1 and the second set of weighting coefficients being a set of spherical coefficients;- storing (106) each second set of weighting coefficients obtained in association with an individual identifier from among the initial set of individuals;wherein each individual of the initial set of individuals is further associated with a set of morphological data, said method further comprising the following steps:- obtaining (107) current morphological data of a new individual;- selecting (109) an individual from among the initial set by comparison between the current morphological data and the sets of morphological data of the individuals of the initial set;- applying (111) a transformation to the second set of weighting coefficients that are associated with the individual selected with a view to obtaining a transformed second set of weighting coefficients, said transformed second set of weighting coefficients being a transformed set of spherical coefficients, the transformation being determined on the basis of the current morphological data with a view to obtaining a modified set of filters;- storing (112) the transformed second set of weighting coefficients in association with an identifier of the new individual.
- Method according to Claim 1, wherein the transformation comprises at least the application of a rotation matrix to the set of spherical coefficients that is associated with the individual selected.
- Method according to Claim 2, wherein the method further comprises the following steps with a view to obtaining the modified set of filters on the basis of the transformed set of spherical coefficients:- applying a homothety, by frequency dilation, to the N independent components, said homothety being determined on the basis of the current morphological data, in order to obtain N transformed independent components;- multiplying the transformed set of spherical coefficients by a matrix formed by the N transformed independent components, with a view to obtaining the modified set of filters in association with the identifier of the new individual.
- Method according to Claim 2, wherein the method further comprises the following steps with a view to obtaining the modified set of filters on the basis of the transformed set of spherical coefficients:- multiplying the transformed set of spherical coefficients by a matrix formed by the N independent components, with a view to obtaining a new set of filters;- applying a homothety by temporally resampling the new set of filters with a view to obtaining the modified set of filters in association with the identifier of the new individual.
- Method according to Claim 4, wherein when the new set of filters is in the frequency domain, the method comprises the application of an inverse Fourier transform to the new set of filters prior to the temporal resampling.
- Method according to one of the preceding claims, wherein the morphological data relate at least to the ear auricle of the user.
- Method according to one of the preceding claims, wherein the binaural filters are transfer functions in the frequency domain, wherein each independent component is a function having a non-zero spectrum in a given frequency band, and wherein the data frequency bands are distinct.
- Method according to Claim 7, wherein the independent components are expressed on a logarithmic scale of frequencies.
- Computer program product comprising program code instructions stored on a medium that is readable by a computer, for the execution of the steps of the method according to any one of Claims 1 to 8.
- Device for processing individualized data representative of the directivity of an audio system, said device (500) comprising a processor configured to:- obtain, via an input interface (501) of the device, for each individual of an initial set of individuals, at least one personalized set of binaural filters;- determine N independent components common to the sets of filters obtained;- decompose each of the sets obtained into a first base formed from the N independent components with a view to obtaining, for each set of filters, a first set of weighting coefficients;- decompose each first set of weighting coefficients into a second base of P independent components, in order to obtain a second set of weighting coefficients, the second base of P independent components being a base of spherical harmonics of order P-1 and the second set of weighting coefficients being a set of spherical coefficients;- storing, in a memory (504) of the device, each second set of weighting coefficients obtained in association with an individual identifier from among the initial set of individuals;wherein each individual of the initial set of individuals is further associated with a set of morphological data, said processor further being configured to:- obtain current morphological data of a new individual;- select an individual from among the initial set by comparison between the current morphological data and the sets of morphological data of the individuals of the initial set;- apply a transformation to the second set of weighting coefficients that are associated with the individual selected with a view to obtaining a transformed second set of weighting coefficients, said transformed second set of weighting coefficients being a transformed set of spherical coefficients, the transformation being determined on the basis of the current morphological data with a view to obtaining a modified set of filters; and- store the transformed second set of weighting coefficients in association with an identifier of the new individual.
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