EP3032536B1 - Filtre vocal adaptatif pour l'atténuation de bruit ambiant - Google Patents

Filtre vocal adaptatif pour l'atténuation de bruit ambiant Download PDF

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Publication number
EP3032536B1
EP3032536B1 EP15198584.3A EP15198584A EP3032536B1 EP 3032536 B1 EP3032536 B1 EP 3032536B1 EP 15198584 A EP15198584 A EP 15198584A EP 3032536 B1 EP3032536 B1 EP 3032536B1
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Prior art keywords
spectral components
energy
signal
spectral
audio signal
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German (de)
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EP3032536A1 (fr
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Tilman Herberger
Titus Tost
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Bellevue Investments GmbH and Co KGaA
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Bellevue Investments GmbH and Co KGaA
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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0264—Noise filtering characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters

Definitions

  • the present invention relates to the general subject matter of creating and analyzing video works and, more specifically, to systems and methods of attenuating ambient noise in a video work.
  • the undesirable component of the signal is might be either automatically determined using a targeted search in the signal for sequences that do not contain speech to use in estimating the undesirable components, or in other cases the user might have to manually select a noise sample (e.g., a section of the sample that contains only the undesirable / background component).
  • a noise sample e.g., a section of the sample that contains only the undesirable / background component.
  • the methods which are already state of the art usually work exclusively in the frequency domain or the time domain.
  • the instant invention utilizes a mixed approach, wherein the digital signal is separated into single spectral components. These frequency components are than transformed back into the time domain, in which the analysis takes place.
  • the instant invention is therefore a method which operates in the frequency domain as well as in the time domain.
  • the instant invention will comprise two separate processes that when combined provide the full functionality of the adaptive speech filter.
  • An embodiment preferably does not require continuous user interaction.
  • An embodiment of a graphical user interface that provides access to the inventive functionality might take many forms.
  • An embodiment of the instant invention preferably starts with the analysis of the input signal.
  • the input signal is broken down into the spectral components with the most energy. This breakdown of the input signal is carried out with a recursive spectral analysis of maxima and minima.
  • the detected spectral components with the most energy are then, in a next preferred step, further analyzed to determine their affiliation to harmonic banks.
  • the behavior of the zero points in the time domain signals of the spectral components with the most energy is analyzed.
  • the filter curve (frequency response) of the adaptive speech filter is calculated. The instant invention utilizes for this calculation the analysis results of the components with the most energy and the analysis results of the zero points.
  • the instant invention initiates the second part, the second process, which is the implementation of the adaptive speech filter.
  • the signal is filtered in the frequency range with an additional filter smoothing in the frequency range.
  • the instant invention further provides pre- and post ringing filters to minimize undesired side effects of the adaptive speech filtering.
  • a first component of the invention involves an analysis of the input signal and generation of an adaptive speech filter.
  • the input signal will be analyzed to identify the spectral components of the signal with the most energy. In an embodiment, this will be done via a recursive spectral analysis that is adapted to find frequencies associated with maxima and minima.
  • the spectral components with the most energy will then be used to (2) determine their association with a harmonic series.
  • One embodiment of the invention will determine the gradient of the spectrum at each of the zero point positions. The variance of each gradient will then be used to help differentiate noise from speech.
  • the variance of each gradient will be used to differentiate the blocks into either a noise or non-noise category. More particularly, in an embodiment if the variance is relatively "high” the associated block will be assigned to a "noise” category. If the variance is intermediate in value, that block will be determined to be mostly speech. Finally, if the variance is relatively “low”, that block will be determined to be non-noise but most likely not associated with speech.
  • the adaptive filter will be applied, preferably in the frequency domain, and in some embodiments additional smoothing will be applied. Additionally, pre- and post- application of the speech filter an anti-ringing filter might be applied to minimize the noise associated therewith. These filters would typically be applied in the frequency domain, followed potentially by some additional smoothing applied to the filtered signal.
  • an embodiment of the present invention preferably begins with the input of a digital signal into a personal or other computer with the input signal being the audio part of a video recording 100.
  • a personal computer would be suitable for use with an embodiment, in reality any computer (including a table, phone, etc.) could possibly be used if the computational power were sufficient.
  • the input signal will be divided into overlapping segments/blocks 110.
  • the audio data might be sampled at a rate of 44 kHz, although other samples rates are certainly possible. That being said, the sample rate and the length of the audio clip will depend on the rate at which the audio was recorded and the length of the recording, whatever that might be.
  • the block length might be a few hundred to several thousand samples in (e.g., 4096 samples) depending on the sample rates.
  • the amount of overlap might be between 0% and 25% of the block size in some embodiments.
  • the windowed input signal will be Fourier transformed using a Fast Fourier transform ("FFT") to transform the audio data into the frequency domain 120.
  • FFT Fast Fourier transform
  • those of ordinary skill in the art will recognize that although the FFT is a preferred method of transforming the data to the frequency domain, a standard Fourier transform could be calculated instead. Additionally, there are any number of other transforms that could be used instead.
  • the Walsh transform and various wavelet-type transforms are known to convert data into a domain where different characteristics of the input signal can be separated and analyzed.
  • the instant invention will calculate the transfer function of the adaptive speech filter 180, preferably in conjunction with the time the input signal is divided into overlapping blocks and windowed and transformed with an FFT 120.
  • the signal is analyzed with a goal of determining the spectral components with the most energy. This is achieved with the recursive maxima-minima analysis.
  • the spectral components so determined are then analyzed in terms of their harmonic series properties (e.g., if the spectral components belong to a harmonic series, the frequencies with the highest spectral maxima would be multiple of the base frequency) and then root/null/nullstelle is determined for each spectral component in order to classify it.
  • the curve of the filter function is determined.
  • the calculated transfer function in some embodiments will be subjected to a temporal equalization 190, e.g., it might be normalized to have unit magnitude, etc.
  • the time constants for that temporal equalization could be, depending of drop or rise, defined separately.
  • the calculated adaptive speech filter function will then be multiplied times the input signal in the frequency domain to attenuate ambient noise 130.
  • an inverse FFT will be calculated on the now-filtered input signal and, following that, in a next preferred step the blocks will be windowed 140 and summed together to generate an output signal 150.
  • An embodiment of the instant invention additionally implements a pre- and/or a post ringing filter which might be added to the workflow before generating the final attenuated digital output signal 160.
  • a pre- and/or a post ringing filter might be added to the workflow before generating the final attenuated digital output signal 160.
  • Such a filter might be necessary because, among others, the calculated spectral components in some instances will be narrow-banded, which would result in the transfer function having corresponding narrow-banded segments. These narrow-banded segments could potentially lead to pre- and post ringing which would take the form of unwanted ambient noise.
  • the pre- and/or post ringing filter(s) will also preferably be implemented in the frequency domain. In most cases this will be a substantially smaller filter order compared to the adaptive speech filter, thus the filter will possesses a higher temporal resolution.
  • the transfer function of the pre- and post ringing filter is calculated by comparing (e.g., by division) the magnitude of the unfiltered input signal with the magnitude of the output signal of the adaptive speech filter. If in specific frequency ranges the output signal contains a substantial higher energy than the unfiltered input signal the instant invention will detect that as a potential pre- or post- ringing of the adaptive speech filter.
  • the transfer function of the pre- and post ringing filter will then be set, in one embodiment, to zero in order to filter out the pre- and post ringing of the adaptive speech filter. After the application of the pre- and post ringing filter the instant invention generates the attenuated output signal 170.
  • this figure illustrates the steps of the calculation of the transfer function of the adaptive speech filter according to one embodiment.
  • the input signal will be split up into the spectral bands with the most energy by using a recursive spectral maxima- minima-analysis that looks for the relevant local maxima (peaks) and minima of the spectrum.
  • a block length of a few hundred or thousand samples e.g., 4096
  • maxima-minima/blocks will be used, more typically between about 10 and 50.
  • the instant invention will determine for closely lying maxima or minima the locally highest or smallest maxima or minima. In a next preferred step the instant invention will determine the spectral components for relevant maxima and adjacent relevant minima. In case of tonal speech components (vowels), these spectral components contain the harmonics of the speech with the most energy 200.
  • the spectral component with the most energy in the frequency domain will be filtered out and will be available as time domain signal as a result.
  • the difference between the filtered signal and the input signal is then used in the next step of the recursive process 205.
  • a recursive process is utilized because it allows the spectral components with the most energy to overlap to thereby increasing the bandwidth of the filter. This also increases the quality of the analysis because a lower bandwidth might potentially distort the result.
  • the recursive process of the instant invention includes a number of steps which are executed recursively.
  • the instant invention executes a high resolution spectrum analysis by splitting the signal into individual blocks, windowing and executing of a Fast Fourier Transform within each block, followed by a calculation of the magnitude of the spectrum (short time power density spectrum).
  • the magnitude will be analyzed to find maxima-and-minima and the local relevant maxima and minima will be determined.
  • the magnitude will be separated into individual spectral components according to the results of the maxima and minima analysis.
  • a next preferred step the spectral component with the most energy will be determined and in the next step this determined spectral component will be transformed back into the time domain with an inverse Fourier Transform, thereby providing the spectral component as time domain signal.
  • a difference signal will be being generated by comparing the input signal and the generated time domain signal - with the difference signal being used as the input signal for the next run-through of the recursive process.
  • the determined spectral components 220 will be, in a next preferred step, analyzed regarding the behavior of the zero points 240. To be more specific and according to the current example, the gradient of the zero point position is calculated in a next preferred step. Additionally, the variance of the scope of the temporal frequency change can also be estimated.
  • the instant invention will implement a classification of the spectral components according to the following scheme.
  • the variances will be interpreted as follows: if the gradient of the zero point has a relatively high variance value then the spectral component will be classified as noise-like, a relatively low value and it will be classified as tonal. In some embodiments, this determination might be made by comparison with a predetermined value. In some instances a statistical analysis of all of the gradients might be employed. In that case, variances that are more than 1 (or 2, etc.) deviations above the average (or median, etc.) gradient value would be characterized as "high”, with variances that are less than, say, 1 (or 2, etc.) standard deviations below the mean being characterized as "low”, with the remainder being classified as intermediate.
  • the spectral component will be being classified as tonal part of the speech signal (vowel). If the variance of the gradient of the zero point is very low then the spectral component will be classified as being tonal but likely not a part of the speech signal. Spectral components of this kind are often caused by regular noise sources (for example air condition, engines, etc.).
  • the instant invention will determine if these spectral components might be associated with a harmonic sequence 260.
  • the determined frequencies with the highest spectral maxima of the spectral components are a multiple of a base frequency.
  • the transfer function of the adaptive speech filter will be computed 265.
  • the results of the analysis regarding harmonic sequences as well as the results of the analysis regarding the behavior of the zero points in the time domain signals of the spectral components will be being used. That being said, the results of these two analyses by themselves might provide erroneous results. For example speech elements may not be determined as such or the speech property is assigned in error to other signal components. With a combination of the results of both analyses the number of erroneous detections is being kept low.
  • the calculation of the filter curve of the adaptive speech filter will be carried as follows. If an association of spectral components to a natural overtone series is detected and more than half of the spectral components assigned to an overtone series have been classified as speech components, all of the spectral components that match with the overtone series will be utilized for the calculation of the adaptive speech filter. The adaptive speech filter is then set to value 1 for all bandwidths of the spectral components. If in the analysis no overtone series is detected and singular spectral components have been classified as speech signals, the adaptive speech filter will be set to value 1 for the bandwidths of these spectral components. In case of fast change of the base frequency, which is typical for speech, the detection of an overtone series sometimes fails. According to this aspect of the invention, an erroneous complete locking of the adaptive speech filter will potentially be prevented.
  • the instant invention provides a substantial improvement for both novice and professional users when editing audio recordings and primarily when attenuating ambient noise in speech signals of video recordings.
  • Embodiments of the invention require minimal user interaction, no definition of multiple parameters or definition of noise samples, it is an automatic process that recursively analyzes the input signal.
  • the improved / isolated speech audio from a noisy video recording can then be, for example, integrated back into the audio track of that recording to improve quality of the recorded speech.
  • the instant invention might be used to reduce ambient noise in hearing aids, intercoms and telephones, etc. More generally such an approach as that taught herein could be used in instances where the computational power and/or memory available to the device is limited and real-time improvement of the audio for purposes of low-latency speech recognition is desirable.
  • the instant invention will provide an automatic mode, which automatically attenuates video recordings in video cameras, therewith providing video recordings with perfect quality audio.
  • Methods of the present invention may be implemented by performing or completing manually, automatically, or a combination thereof, selected steps or tasks.
  • method may refer to manners, means, techniques and procedures for accomplishing a given task including, but not limited to, those manners, means, techniques and procedures either known to, or readily developed from known manners, means, techniques and procedures by practitioners of the art to which the invention belongs.
  • the term "at least” followed by a number is used herein to denote the start of a range beginning with that number (which may be a ranger having an upper limit or no upper limit, depending on the variable being defined). For example, “at least 1” means 1 or more than 1.
  • the term “at most” followed by a number is used herein to denote the end of a range ending with that number (which may be a range having 1 or 0 as its lower limit, or a range having no lower limit, depending upon the variable being defined). For example, “at most 4" means 4 or less than 4, and "at most 40%” means 40% or less than 40%.
  • a range is given as "(a first number) to (a second number)" or "(a first number) - (a second number)"
  • 25 to 100 should be interpreted to mean a range whose lower limit is 25 and whose upper limit is 100.
  • every possible subrange or interval within that range is also specifically intended unless the context indicates to the contrary.
  • ranges for example, if the specification indicates a range of 25 to 100 such range is also intended to include subranges such as 26 -100, 27-100, etc., 25-99, 25-98, etc., as well as any other possible combination of lower and upper values within the stated range, e.g., 33-47, 60-97, 41-45, 28-96, etc.
  • integer range values have been used in this paragraph for purposes of illustration only and decimal and fractional values (e.g., 46.7 - 91.3) should also be understood to be intended as possible subrange endpoints unless specifically excluded.
  • the defined steps can be carried out in any order or simultaneously (except where context excludes that possibility), and the method can also include one or more other steps which are carried out before any of the defined steps, between two of the defined steps, or after all of the defined steps (except where context excludes that possibility).
  • the defined steps can be carried out in any order or simultaneously (except where context concludes that possibility), and the method can also include one or more other steps which are carried out before any of the defined steps, between two of the defined steps, or after all of the defined steps (except where context concludes that possibility).

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
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Claims (11)

  1. Une méthode qui consiste à améliorer un signal de voix parlée comportant du bruit et qui englobe les étapes suivantes :
    réalisation, au moyen de matériel de traitement informatique, d'opérations de :
    a. lecture d'un signal audio contenant le signal de voix parlée
    b. transformation du signal audio vers le domaine fréquentiel et formation d'un signal audio transformé
    c. détermination, au moyen d'une analyse spectrale récursive dans le domaine fréquentiel, des composants spectraux les plus énergiques du signal audio transformé
    d. détermination de points zéro dans le domaine temporel pour chacun des composants spectraux déterminés comme les plus énergiques
    e. calcul du gradient de chacun des points zéro déterminés pour chacun des composants spectraux déterminés comme les plus énergiques
    f. calcul de la variance de chacune des valeurs de gradient déterminées pour chacun des composants spectraux déterminés comme les plus énergiques
    g. analyse de la variance de chacun des gradients calculés pour chacun des composants spectraux déterminés comme les plus énergiques et attribution à chacun des composants d'au moins une d'une pluralité de catégories
    h. constatation si chacun des composants spectraux déterminés comme les plus énergiques appartient à une série harmonique
    i. calcul d'une courbe de filtre pour chacun des composants spectraux déterminés comme les plus énergiques en utilisant l'analyse de la variance des valeurs de gradient et constatation si les composants appartiennent à la série harmonique
    j. application de la courbe de filtre à chacun des composants spectraux déterminés comme les plus énergiques et application de la courbe de filtre au signal audio transformé, formant ainsi un signal audio filtré
    k. transformation inverse du signal audio filtré, formant ainsi le signal de voix parlée amélioré.
  2. Une méthode qui équivaut à la revendication 1, l'étape (c) englobant les étapes suivantes :
    (c1) mise en œuvre d'une analyse spectrale de haute résolution pour le signal audio
    (c2) détermination du spectre de densité de puissance à court terme, c'est-à-dire de l'amplitude
    (c3) détermination des maxima et minima locaux de l'amplitude déterminée
    (c4) segmentation de l'amplitude en composants spectraux uniques conformément à la détermination des maxima et minima locaux
    (c5) détermination du composant spectral le plus énergique parmi les composants spectraux uniques segmentés
    (c6) transformation du composant spectral dans le domaine temporel, générant ainsi un signal de domaine temporel
    (c7) génération d'un signal différentiel entre le signal audio et le signal de domaine temporel généré
    (c8) utilisation du signal différentiel lors de la prochaine exécution des étapes (c1) à (c7).
  3. Une méthode qui équivaut à la revendication 1, l'étape (g) englobant l'étape suivante :
    (g1) segmentation des catégories en catégories pour les valeurs de gradient avec des valeurs de variance élevées, catégories pour les valeurs de gradient avec des valeurs de variance moyennes et catégories pour les valeurs de gradient avec des valeurs de variance faibles.
  4. Une méthode qui équivaut à la revendication 3, les composants spectraux déterminés comme les plus énergiques dont les valeurs de gradient présentent des valeurs de variance élevées étant considérés comme bruyants
  5. Une méthode qui équivaut à la revendication 3, les composants spectraux déterminés comme les plus énergiques dont les valeurs de gradient présentent des valeurs de variance moyennes étant considérés comme faisant partie d'une partie tonale du signal d'entrée
  6. Une méthode qui équivaut à la revendication 3, les composants spectraux déterminés comme les plus énergiques dont les valeurs de gradient présentent des valeurs de variance faibles étant considérés comme une partie tonale du signal d'entrée, et non comme faisant partie du signal de voix parlée
  7. Une méthode qui équivaut à la revendication 1, l'étape (i) englobant l'étape suivante :
    i1) si une appartenance des composants spectraux déterminés comme les plus énergiques à une série harmonique a été constatée et si plus de la moitié de ces composants ont été considérés comme faisant partie d'une partie tonale du signal d'entrée, utilisation de tous les composants dans le calcul de la courbe de filtre, puis paramétrage du filtre à un état ouvert pour toutes les largeurs de bande des composants.
  8. Une méthode qui équivaut à la revendication 1, l'étape (i) englobant l'étape suivante :
    i2) si une appartenance des composants spectraux à une série harmonique n'a pas été constatée et si les composants spectraux uniques déterminés comme les plus énergiques ont été considérés comme faisant partie d'une partie tonale du signal d'entrée, paramétrage du filtre à un état ouvert pour les largeurs de bande des composants.
  9. Une méthode qui équivaut à la revendication 1, l'étape (j) englobant l'étape suivante :
    j1) multiplication du spectre complexe par la courbe de filtre pour chacun des composants spectraux déterminés comme les plus énergiques.
  10. Une méthode qui équivaut à la revendication 1, l'étape (k) englobant l'étape suivante :
    k1) utilisation d'un algorithme FFT inverse pour la transformation inverse
    k2) fenêtrage et agrégation de chaque composant spectral individuel,
    formant ainsi le signal de voix parlée amélioré.
  11. Une méthode qui équivaut à la revendication 1, cette dernière englobant en outre les étapes suivantes :
    l) détermination de l'amplitude du signal de voix parlée amélioré
    m) détermination de l'amplitude du signal audio
    n) comparaison de l'amplitude du signal audio avec l'amplitude du signal de voix parlée amélioré
    o) si l'amplitude du signal de voix parlée amélioré est significativement plus élevée dans une pluralité de plages de fréquences que l'amplitude du signal audio, paramétrage d'un filtre avant et après suroscillation à un état fermé afin de filtrer les différences.
EP15198584.3A 2014-12-12 2015-12-09 Filtre vocal adaptatif pour l'atténuation de bruit ambiant Active EP3032536B1 (fr)

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Publication number Priority date Publication date Assignee Title
US6097820A (en) * 1996-12-23 2000-08-01 Lucent Technologies Inc. System and method for suppressing noise in digitally represented voice signals
JP5141542B2 (ja) * 2008-12-24 2013-02-13 富士通株式会社 雑音検出装置及び雑音検出方法
EP2828855B1 (fr) * 2012-03-23 2016-04-27 Dolby Laboratories Licensing Corporation Détermination d'une mesure d'harmonicité pour traitement vocal
US9386371B2 (en) * 2012-06-08 2016-07-05 Apple Inc. Psychoacoustic adaptive notch filtering

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