Classifications

• • 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
  • G10L25/78—Detection of presence or absence of voice signals
• • 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
  • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
  • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
  • G10L19/06—Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients
• • 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
  • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
  • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
  • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
• • 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
  • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
  • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
  • G10L19/26—Pre-filtering or post-filtering
• • 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
  • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
  • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders

Definitions

• the present invention relates generally to the field of sound data processing.
• This processing is adapted in particular to the transmission and / or storage of multimedia signals such as audio signals (speech and / or sounds).
• the present invention more specifically aims at analyzing an audio signal resulting from such a treatment.
• Such a processing comprises a coding phase of linear prediction type LPC (abbreviation of Linear Predictive Coding).
• LPC abbreviation of Linear Predictive Coding
• encoders use signal properties such as its harmonic structure, exploited by long-term prediction filters, as well as its local stationarity, exploited by short-term prediction filters.
• the speech signal can be considered as a stationary signal for example over time intervals of 10 to 20 ms. It is therefore possible to analyze this signal by sample blocks called frames, after an appropriate windowing.
• the short-term correlations can be modeled by time-varying linear filters whose coefficients are obtained by means of a linear prediction analysis on frames, of short duration (from 10 to 20 ms in the aforementioned example ).
• LPC linear prediction coding is one of the most widely used digital coding techniques, in particular in the mobile telephony sector, in particular in the 3GPP AMR-WB coder as described in the document "3GPP TS 26.190 V10.0.0". (201 1 -03) 3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Speech coded speech processing functions; Adaptive Multi-Rate - Wideband (AMR-WB) coded speech; Transcoding functions (Release 10) ".
• the LPC coding consists in performing an LPC analysis of the signal to be coded in order to determine an LPC filter, then in quantifying this filter, on the one hand, and in modeling and coding the excitation signal, on the other hand.
• the autoregressive P-order linear prediction model consists in determining a signal sample at an instant n by a linear combination of the past P samples (prediction principle).
• the short-term prediction filter denoted by A (z), models the spectral envelope of the signal:
• the coefficients a, of the filter must be transmitted to the receiver. However, since these coefficients do not have good quantization properties, transformations are preferentially used. Among the most common are:
• LSP coefficients are now the most used for the representation of the LPC filter because they are well suited for vector quantization.
• linear prediction coding technique allows a substantial reduction of the bit rate in favor of high audio quality.
• linear prediction coding is poorly suited to certain coded audio signal processing applications, such as detecting a predetermined frequency band in such coded signals.
• PCM Pulse Code Modulation
• Transcoding is necessary when in a transmission chain, a compressed signal frame emitted by an encoder can no longer continue in this format. Transcoding makes it possible to convert this frame into another format compatible with the rest of the transmission chain.
• the most basic solution (and the most common at the moment) is the end-to-end addition of a decoder and an encoder.
• the compressed frame arrives in a first format, then it is decompressed.
• the decompressed signal is then compressed again in a second format accepted later in the communication chain. This cascading of a decoder and an encoder is called a tandem.
• an encoder operating in an enlarged frequency band [50Hz-7kHz], also called WB (WideBand) may be required to encode an audio content operating in a narrower frequency band than the enlarged band.
• WB WideBand
• the content to be encoded by a 3GPP AMR-WB encoder as mentioned above, although sampled at 16 kHz, may be in fact only in a telephone band if such content has been encoded previously by an encoder operating in a narrow frequency band [300 Hz, 3400 Hz], also known as the NB band (abbreviation of "NarrowBand").
• the limited quality of the acoustics of the transmitting terminal can not cover the entire enlarged band. It thus appears that the audio band of an encoder-encoded stream operating on sampled signals at a given sampling frequency may be much more restricted than that actually supported by the encoder.
• the detection of the frequency band in the signal domain is based on a spectral analysis of the digital audio signal.
• a detection is implemented in the 3GPP2 codec VMR-WB as described in the document 3GPP2 C.S0052-0 (June 1 1, 2004) Source-Controlled Variable-Rate Multimode Wideband Speech Coded (VMR-WB) Service Option 62 for Spread Spectrum Systems ", to detect narrow-band audio content that has been oversampled at the 16 kHz sampling frequency specific to that codec.
• the above-mentioned codec carries out a spectral analysis of the temporal signal (after sub-sampling at 1 2.8 kHz, high-pass filtering and pre-emphasis) by performing two FFT frequency transforms on 256 samples per frame, to obtain two sets of spectral parameters per frame.
• a detection algorithm is applied to detect such signals. It consists of testing the level of smoothed energy in the last two bands.
• FFT transform As an alternative to the above-mentioned FFT transform, other frequency transforms may be used, such as, for example, the Modified Discrete Cosine Transformation (MDCT).
• MDCT Modified Discrete Cosine Transformation
• the detection of the frequency band in the coded domain can be based on a prior decoding of the coded signal and then on the application of the spectral analysis techniques above as used in the signal domain to analyze the audio contents. originals (not coded or before coding).
• decoding increases the complexity and delay of processing. In many applications, it is therefore desirable, in order to avoid these problems of complexity and / or of delay, to extract the characteristics of the signal without performing a complete decoding of the signal.
• Several analysis techniques in the coded domain have been proposed. They concern transform or sub-band encoders such as MPEG coders (eg MP3, AAC, ).
• the coded stream indeed comprises coded spectral coefficients, such as, for example, the MDCT coefficients in the MP3 encoder.
• coded spectral coefficients such as, for example, the MDCT coefficients in the MP3 encoder.
• ⁇ SMRS i, where S j represents the ith coefficient of the i th band and
• N t the number of coefficients in the band
• T SRMS a threshold
• the methods for detecting the frequency band of a digital audio signal which have just been described are mainly based on a frequency analysis of the signal spectrum.
• the detection of the audio frequency band in the coded content advantageously exploits the spectral information contained in the coded bitstream by not completely decoding the signal. This significantly reduces the complexity of the detection by eliminating the costly operations required for full decoding and spectral analysis (FFT or MDCT based) of the encoded audio signal.
• the decoded signal is available, such as for example the application of displaying on a mobile terminal a logo " HD Voice ", this is not the case for all applications.
• the complexity of the decoding in an encoder, such as in particular the aforementioned AMR-WB encoder, the decoding represents 20% of the total complexity of the encoder, itself estimated around 40 WMOPS (abbreviation of "Weighted Millions of Operations Per Second”). ).
• linear prediction coding techniques with other compression techniques such as, for example, MDCT-type frequency transform coding techniques. It would then be sufficient to perform the detection on the blocks of audio signal encoded by a frequency transform technique using for these blocks a state of the art method. However this solution would harm the reactivity of the detection because depending on the type of the content and / or the bit rate, the linear prediction coding may be mainly used.
• One of the aims of the invention is to overcome disadvantages of the state of the aforementioned techniques.
• an object of the present invention relates to a method for detecting a predetermined frequency band in an audio data signal which has been coded according to a succession of data blocks, of which at least some blocks respectively contain at least a set of spectral parameters representing a linear prediction filter.
• the method according to the invention is remarkable in that it implements, for a current block among said at least some blocks and at least a plurality of spectral parameters of said set have been previously decoded, the steps of:
• Such an arrangement makes it possible to identify, with a low cost of calculations, whether the audio frequency band of a content previously coded by a linear prediction coder is more restricted or not than the audio frequency band in which such an encoder operates. .
• the invention makes it possible, for example, to determine the presence of 'audio content above 4 kHz.
• the invention can be advantageously implemented in certain frequency band detection applications that do not need to perform a decoding of the coded audio signal, such as for example the indicator of numbers of calls deposited in broadband on a mobile voice mail.
• all the spectral parameters of the above set of spectral parameters are previously decoded.
• Such an arrangement makes it possible to detect in a simple manner the frequency band of a decoded audio content, by direct access to the decoded linear prediction parameters associated with this content, and without adding any additional complexity (complete decoding, time-frequency transform) .
• the invention is particularly adapted to its implementation in a communication terminal, fixed or mobile, which comprises by nature an encoder and an audio decoder, and more specifically to the application in this terminal which consists in display on the screen of the latter a logo "HD Voice".
• some blocks each contain a set of spectral parameters representing a linear prediction filter and some other blocks each contain a set of spectral parameters obtained by frequency transformation.
• the blocks each containing a set of spectral parameters representing a linear prediction filter are considered the blocks each containing a set of spectral parameters representing a linear prediction filter.
• a frequency band detection method of the prior art may for example be applied.
• the determining step consists in preferably searching for the index of the first spectral parameter greater than a threshold frequency.
• the term high frequency band the frequency band above a certain threshold.
• the high frequency band corresponds to frequencies greater than 4 kHz (or 3.4 kHz). More generally, for a signal sampled at a sampling frequency Fe and a bandwidth less than or equal to 0.5 Fe, the high frequency band will be the frequency band greater than a'0.5Fe (0 ⁇ a ' ⁇ 1), a 'being adjustable.
• the term low frequency band the frequency band below a certain threshold.
• said determining step consists in preferably searching for the index of the last spectral parameter lower than a threshold frequency.
• Such an arrangement thus makes it possible to implement the invention for example in speech processing applications in HD quality, in particular both in a mobile communication terminal capable of operating in the aforementioned frequency range, and in a server. voicemail capable of processing HD audio content, or even within a probe being in audio stream cutoff of a communication network.
• the current block contains data representative of a voice activity.
• Such an optional arrangement makes it possible, in the particular case where it is a question of detecting in the coded audio signal a band situated in the high frequencies, to optimize the reduction of the complexity of the detection method by carrying out the detection, not on all the frames containing at least one set of spectral parameters representing a linear prediction filter, but only on relevant frames likely to contain high frequencies, that is to say those likely to contain voice and / or music data.
• the criterion is calculated by comparison between:
• Such an arrangement makes it possible to perform, from a simple calculation, if the predetermined frequency band is detected, while respecting a compromise complexity / reliability / reactivity of the detection.
• the aforementioned criterion is calculated using a mathematical function using as parameter at least the index of the first decoded spectral parameter that was obtained at the end of the aforementioned determination step.
• a global decision step is implemented by smoothing the result of this decision step and K decision results. previous, relating respectively to K blocks preceding the current block.
• Such multi-block smoothing of the local detections specific to each block thus makes it possible to increase the reliability of the detection and for example to protect itself from a really narrow band audio content during a few frames (noise, for example).
• the invention relates to a detection device for implementing the detection method according to the invention.
• the detection device according to the invention is therefore intended to detect a predetermined frequency band in an audio data signal which has been coded according to a succession of data blocks, among which at least some blocks respectively contain at least one set of parameters.
• spectrals representing a linear prediction filter Such a detection device is remarkable in that it comprises means for processing a current block among said at least some blocks and of which at least a plurality of spectral parameters of said set have been previously decoded, which means are able to:
• the detection device is intended to implement all the embodiments of the detection method which have been mentioned above.
• the detection device is adapted to be contained in a communication terminal, in a voicemail server or in a probe.
• the invention also relates to a computer program comprising instructions for executing the steps of the detection method above, when the program is executed by a computer.
• Such a program can use any programming language, and be in the form of source code, object code, or intermediate code between source code and object code, such as in a partially compiled form, or in any another desirable form.
• Still another object of the invention is directed to a computer readable recording medium, and including computer program instructions as mentioned above.
• the recording medium may be any entity or device capable of storing the program.
• a medium may comprise storage means, such as a ROM, for example a CD ROM or a microelectronic circuit ROM, or a magnetic recording medium, for example a floppy disk or a Hard disk.
• such a recording medium can be a transmissible medium such as an electrical or optical signal, which can be routed via an electrical or optical cable, by radio or other means.
• the program according to the invention can be downloaded in particular on an Internet type network.
• such a recording medium may be an integrated circuit in which the program is incorporated, the circuit being adapted to execute the method in question or to be used in the execution of the latter.
• the aforementioned detection device and computer program have at least the same advantages as those conferred by the detection method according to the present invention.
• FIG. 1 represents the main steps of the detection method according to the invention
• FIG. 2 represents an embodiment of a detection device according to the invention
• FIG. 3 represents various examples of threshold frequency values used in the method and the detection device according to the invention.
• FIG. 4B represents a histogram of the index of the first spectral parameter greater than 4 kHz, for all the blocks coded by the AMR-WB coder, without taking into account the indication of vocal activity,
• FIG. 5A represents a cumulative histogram of the ratio between the maximum difference and the minimum difference between two successive spectral parameters from the index of the first spectral parameter greater than 4 kHz, for the blocks encoded by the AMR-WB encoder containing data.
• FIG. 5B represents a cumulative histogram of the ratio between the maximum difference and the minimum difference between two successive spectral parameters from the index of the first spectral parameter greater than 4 kHz, for all the blocks coded by the AMR-WB coder, without take into account the voice activity indication
• FIG. 6A represents a mobile communication terminal able to implement the detection method as represented in FIG. 1;
• FIG. 6B represents a voicemail server able to implement the detection method as represented in FIG. 1.
• the frequency band detection method according to the invention is represented in the form of an algorithm comprising steps S0 to S4.
• the aforementioned detection method is implemented in a software or hardware way in a DET detection device represented in FIG. 2, which comprises for this purpose a processing module TR specific to the detection.
• such a detection device DET In order to detect a predetermined frequency band in a given audio signal, such a detection device DET is intended to be arranged:
• the detection device DET is for example contained in a fixed or mobile communication terminal.
• the detecting device DET is for example contained in an element of the transmission chain of the audio signal (ex : mail server in which audio messages are stored without decoding).
• this signal is coded, which was first sampled at a predetermined sampling frequency Fe.
• the coding of said signal is carried out for example in a linear prediction coder using short-term LPC spectral parameters, such as ISP coefficients or an associated representation, covering at least part of the frequency spectrum (normalized or no).
• short-term LPC spectral parameters such as ISP coefficients or an associated representation
• Said coder is for example the 3GPP AMR-WB encoder, as mentioned above in the description.
• the coding of said signal could be carried out by an encoder such as, for example, that which was mentioned above in the description, which combines a frequency transformation technique of the MDCT type and a linear prediction coding technique of type CELP.
• the sampling frequency is equal to 16 kHz, corresponding to the nominal sampling frequency of the AMR-WB encoder operating in the useful band of 50 Hz to 7 kHz.
• a plurality Z of consecutive blocks of data Bi, B 2 , B z are obtained, as shown in FIGS. 1 and 2.
• a plurality of consecutive blocks of data some of said blocks containing at least one set of spectral parameters representing a linear prediction filter and some others of said blocks containing at least one set of spectral parameters obtained by frequency transform.
• the detection method according to the invention applies only to the blocks which contain at least one set of spectral parameters representing a linear prediction filter, a plurality of these parameters having been previously decoded.
• a frequency band detection method of the prior art may for example be applied.
• the predetermined frequency band is the HF band of an expanded band content.
• a current block B n is processed (where n is an integer such that 1 ⁇ n ⁇ Z).
• the current block B n contains M previously decoded spectral parameters p (i k ), having an ordered subset of M '(M' ⁇ M) spectral parameters which extends for example between the indices i min and i max , such that p (i min ) ⁇ ... ⁇ p (i k ) ⁇ ... ⁇ p (i max ), where i min represents the index of the smallest spectral parameter of said subset and i max represents the subscript of the largest spectral parameter of said subset.
• the spectral parameters of the ordered subset satisfy the relation: p (i) ⁇ p (j) if i ⁇ j, i, j G ⁇ imin, imax ⁇ - H It is obvious to those skilled in the art that the invention also applies to other cases: for example, the case where the spectral parameters of the ordered subset satisfy the relation: p (i)> p ( j) if i ⁇ j, i, j G ⁇ imin, imax ⁇ -
• step S1 is implemented by a first calculation software sub-module CAL1 of the detection device DET, as represented in FIG. 2.
• the calculation sub-module CAL1 determines, among said M 'spectral parameters, the index / of the first spectral parameter which is the most close to a threshold frequency, said threshold frequency being determined from the sampling frequency F e of said audio signal.
• FIG. 3 represents different possible values of F th according to the sampling frequency F e used and the value of the parameter a.
• step S1 the calculation sub-module CAL1 searches for the index Î H F of the first spectral parameter p (i k ) greater than F th according to the following operation:
• step S1 the calculation sub-module CAL1 searches for the index IBF of the last spectral parameter p (i) less than F t h according to the following operation:
• the step S1 is preceded by a preselection step S0, during which are preselected, among the blocks Bi, B 2 , B z , only blocks that contain data representative of a voice activity.
• VAD Voice Activity Detection
• VAD indicator 1 in the coded block, "DTX on” mode of the discontinuous transmission module DTX (abbreviation of "Discontinuous Transmission”), classification of the block coded as containing a voice activity when the block has been encoded by an Enhanced Variable Rate CODEC (EVRC)
• EVRC Enhanced Variable Rate CODEC
• the preselection step S0 is implemented by a PRES preselection software module represented in FIG. 2.
• step SO being optional, it is shown in dotted line in FIG. 1.
• the module PRES of FIG. 2 is also represented in dashed line.
• step S2 the calculation of at least one criterion from said index /> determined.
• step S2 the calculation of at least one criterion from said index /> determined.
• step S2 is implemented by a second calculation software sub-module CAL2 of the detection device DET, as represented in FIG. 2.
• such a criterion is based on the comparison of the "distance" between two successive spectral parameters with respect to the index i F determined.
• such a distance corresponds to the simple difference between two successive spectral parameters:
• this criterion is the ratio p between the two distances calculated previously, such that:
• such a criterion is based on a mathematical function F (/) using the index i F as parameter.
• Said mathematical function F (>) consists for example of a piecewise affine function such that:
• said function can be in four pieces, such as:
• the criterion depends on the value of the affine function.
• a step S3 represented in FIG. 1 consists in deciding whether the predetermined frequency band is detected in the current block B n , as a function of one of the criteria which has been calculated on the basis of FIG. step S2.
• Such a step is implemented by a third calculation software sub-module CAL3 of the detection device DET, as represented in FIG. 2.
• the decision is based on one or the other of the two criteria mentioned above, or a combination thereof.
• the decision step relates to the detection of a band of high frequencies is described below. It is obvious to one skilled in the art to apply this decision step in a similar manner, with regard to the detection of another frequency band, such as for example a low frequency band.
• the hard decision consists in comparing the criterion p with a predetermined threshold adaptive or not, noted critth.
• the comparison is for example made according to the calculations below:
• flag H F is a bit that is either set to indicate that the RF content has been detected, or set to 0 to indicate that the RF content has not been detected.
• a flexible decision is for example to use the value of p bounded in the interval [1, 3]. The closer this value is to the lower bound "1" of this interval, the more HF content is considered undetected in the block of the audio signal. The closer this value is to the upper bound "3" of the interval, the more HF content is considered detected in the audio signal.
• the hard decision consists in comparing the criterion p 'with a predetermined threshold adaptive or not, noted crit' th - The comparison being then:
• flagHF 1 (respectively 0) indicates that the RF content has been detected, (or that the RF content has not been detected).
• the soft decision is for example to use the value of p 'in the interval [0, 1].
• the more the value of the criteria is close to the limits of the interval the more the decision for the block (detection or not of HF content) appears reliable, while a value of p 'close to the threshold crit'th indicates a low reliability of the decision.
• the decision can also be flexible or hard.
• a hard decision is for example to compare the criterion F (/ HF) to 0, according to the calculations below:
• flag H F is a bit that is either set to indicate that the RF content has been detected, or set to 0 to indicate that the RF content has not been detected.
• the soft decision can then consist in taking the value of the mathematical function.
• This value is negative (respectively positive), the greater the reliability of the detection of the presence (or lack thereof) of an RF content is high.
• a value of the mathematical function close to zero indicates that the reliability of the detection is low.
• step S4 smoothing these K results and the result of the decision that has just been obtained for the current block B n in the above-mentioned step S3 by a possibly slippery window.
• detection on the window may be a soft or hard decision, as the local detections for each block were obtained by soft or hard decision.
• smoothing step S4 is implemented by a fourth calculation software sub-module CAL4 shown in FIG. 2.
• Step S4 being optional, it is shown in dotted line in FIG.
• the submodule CAL4 of Figure 2 is also shown in dashed line.
• each coded data block contains 16 parameters, the first 15 of which are ordered spectral parameters covering the (normalized) spectrum between 0 and 6.4 kHz, the sixteenth parameter being the one-bit voice activity indicator (VAD).
• VAD voice activity indicator
• the indices are represented on the abscissa and the percentage distribution of these indices is represented on the ordinate.
• the detection method that has been implemented comprises the step S0 of preselecting the blocks containing a voice activity.
• Fig. 4B the detection method that has been implemented does not include step S0.
• Four different configurations are represented by way of example in FIGS.
• the values of the ratio p are represented on the abscissa and the distribution as a percentage of these ratios are represented on the ordinate.
• the detection method that has been implemented comprises the preselection step SO of the blocks containing a voice activity.
• Fig. 5B the detection method that has been implemented does not include step SO.
• Four configurations, which respectively correspond to those of FIGS. 4A and 4B, are shown in FIGS. 5A and 5B. The four configurations of FIGS. 5A and 5B are symbolized in the same manner as in FIGS. 4A and 4B.
• the distribution of the ratio p differs significantly according to whether the encoder is of WB or NB type.
• Such a terminal is designated by the reference TER in FIG. 6A.
• the TER terminal comprises:
• an INT user interface conventionally comprising a keyboard, a screen, a microphone and a loudspeaker
• a communication module COM1 for example of the 3G type
• a memory MEM1 comprising an audio coding module CO1 and an audio decoding module DO1.
• the coding module CO1 and the decoding module DO1 are of the AMR-WB type.
• the ROM MEM1 or another memory of the mobile terminal TER further contains a DET1 device for detecting a predetermined frequency band, similar to the detecting device DET shown in FIG. 2.
• a coded audio stream is received by the communication module COM1, then completely decoded by the decoding module D01, so that the mobile terminal TER renders the speech via the loudspeaker. speaker of its INT user interface.
• the decoded parameters delivered by the decoder D01 to the detection device DET1 are the first 15 ISF coefficients, ordered spectral parameters covering the (normalized) spectrum between 0 and 6.4 kHz, and possibly the VAD indicator whose value is set to 1 if the encoder of the terminal that sent the coded audio stream to the terminal TER estimated that the signal of the frame was active (tone, speech, music), or zero otherwise.
• the detection device DET1 of the terminal TER then directly implements the predetermined frequency band detection method as described in FIG. 1, with low complexity. much lower for example the complexity of the application of a time-frequency transform on the previously decoded signal.
• a current block B n is processed (n being an integer such that 1 ⁇ n ⁇ Z).
• the current block B n contains the fifteen / sixteen aforementioned parameters (15 spectral coefficients and possibly the VAD indicator) which have been decoded by the decoding module D01.
• the step S1 is preceded by the preselection step S0, during which are preselected, among the blocks B ; B 2 , ..., B z , only blocks that contain data representative of a voice activity, for which the VAD flag is 1.
• the index H H F of the first spectral parameter p (i k ) greater than F th is searched in accordance with the following operation:
• the threshold frequency F t h is equal to 4 kHz.
• critl_oc L_negate (critl_oc);
• a step S3 represented in FIG. 1 consists in deciding whether the predetermined frequency band is detected in the current block B n , as a function of one of the criteria which has been calculated on the basis of FIG. step S2.
• the decision is a flexible decision given by the local criterion calculated in the previous step.
• the HD logo is intended to be displayed on the TER terminal screen with a higher or lower contrast which respectively corresponds to a higher or lower value of the calculated criterion.
• the decision is a hard decision determined by the local criterion calculated in the previous step.
• decLoc 1; move16 (); / * WB * /
• the HD logo is intended to be displayed on the TER terminal screen if the calculated criterion is less than 0, or not to be displayed otherwise.
• the local detections are smoothed over several blocks (nbCount> 1) by a possibly slippery window.
• the detection on the window may be a soft or hard decGIob decision, whether the local detections were obtained by soft or hard decision.
• critGlob L_sub (critGlob, tabDec nd]);
• critGlob L_add (critGlob, decLoc);
• the overall decision is made on non-overlapping windows.
• there is no need to store a local decision array just add the local decisions to the global criterion that is reset to zero at the beginning of each processed window.
• critGlob L_add (critGlob, decLoc);
• Such a server is designated SER in FIG. 6B.
• such a server conventionally comprises:
• a communication module COM2 for example of IP type
• a memory MEM2 which contains a GES module for managing the voice messages recorded in the inboxes of the aforementioned EBR set.
• the memory MEM2 furthermore contains a decoding module DO2 and a coding module CO2 which are destined respectively to decode and re-encode the audio content of the voice message deposited.
• a decoding module DO2 and a coding module CO2 which are destined respectively to decode and re-encode the audio content of the voice message deposited.
• Such an operation is necessary for example in the case where the audio content of the voice message deposited was initially coded by an encoder which is different from the encoder contained in the terminal intended to consult said voice message or proposed by the network during the consultation of said message.
• Such an operation may also be necessary in order to store a voice message deposited in a different coding format, which may be an operator's choice for an application such as webmail, which aims to propose the message on the mailbox of the owner of the voicemail.
• the memory MEM2 or another memory of the SER server also contains:
• a device DET2 for detecting a predetermined frequency band similar to the detection device DET shown in FIG. 2
• a partial decoding module DP a partial decoding module DP.
• the partial decoding module DP is able, prior to the detection of the RF content, to decode only part of the first 15 ISF coefficients and possibly the VAD indicator.
• Such an arrangement is possible taking into account the vector quantization of the ISF coefficients according to two sub-vectors, as implemented in an AMR-WB type encoder.
• the decoding module DP decodes only the second sub-vector of the ISF coefficients, that is to say the one containing the last eight highest index ISF coefficients, whose distribution is more likely to demonstrate the presence of HF content.
• the decoding module DP decodes the VAD indicator.
• Such an arrangement advantageously makes it possible to reduce the computational complexity of detecting the frequency band of the coded audio stream.
• Such an arrangement also makes it possible to save the resources of the memory MEM2 by eliminating the decoding instructions of the first sub-vector of the ISF coefficients and the storage of its vector quantization dictionaries.
• the detection device DET2 of the server SER then directly implements the predetermined frequency band detection method as described in FIG.
• the fact of limiting the decoding to only a part of the spectral parameters advantageously makes it possible, in favor of a low processing cost, to identify on the frames coded by a linear prediction coder such as the AMR-WB, if the coded content has indeed high frequency components and therefore if it is really HD and thus have relevant information of the audio band contents at a system not performing decoding of the streams binaries (such as a voicemail server).
• a linear prediction coder such as the AMR-WB
• the decoding module DP then functions in the same way as the decoding module D01 which has been described with reference to FIG. 6A.
• the method for detecting a predetermined frequency band is not necessarily limited to the contents coded by an enlarged band coder. This bandwidth can also be variable.
• the detection method could be implemented to detect low frequency band content instead of high frequency band content.
• the above-mentioned determination step S2 would naturally consist of searching, among at least a plurality of previously decoded spectral parameters of the set of spectral parameters, of the index of the largest spectral parameter less than a threshold frequency. .
• the threshold frequency F t h may also vary during one of the aforementioned applications.
• the detection method can also be implemented according to several variants, both in the choice of criteria, in the manner of possibly combining several criteria, or in the use of soft or hard decisions, both locally and globally. Depending on the variant selected, it is then possible to optimize the complexity / reliability / reactivity compromise of the detection.

Landscapes

• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• Computational Linguistics (AREA)
• Signal Processing (AREA)
• Health & Medical Sciences (AREA)
• Audiology, Speech & Language Pathology (AREA)
• Human Computer Interaction (AREA)
• Acoustics & Sound (AREA)
• Multimedia (AREA)
• Spectroscopy & Molecular Physics (AREA)
• Compression, Expansion, Code Conversion, And Decoders (AREA)

Applications Claiming Priority (2)

Publications (2)

Family

ID=47599055

Family Applications (1)

Country Status (5)

Cited By (1)

Families Citing this family (5)

Family Cites Families (5)

• 2011
  • 2011-12-20 FR FR1161992A patent/FR2984580A1/fr not_active Withdrawn
• 2012
  • 2012-12-11 CN CN201280070157.0A patent/CN104137179B/zh active Active
  • 2012-12-11 EP EP12816709.5A patent/EP2795618B1/de active Active
  • 2012-12-11 US US14/367,435 patent/US9431030B2/en active Active
  • 2012-12-11 WO PCT/FR2012/052882 patent/WO2013093291A1/fr active Application Filing
• 2015
  • 2015-12-10 US US14/965,528 patent/US9928852B2/en active Active

Also Published As

Similar Documents

Legal Events