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
  • 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
  • G10L19/008—Multichannel audio signal coding or decoding using interchannel correlation to reduce redundancy, e.g. joint-stereo, intensity-coding or matrixing
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S7/00—Indicating arrangements; Control arrangements, e.g. balance control
  • H04S7/30—Control circuits for electronic adaptation of the sound field
  • H04S7/307—Frequency adjustment, e.g. tone control
• • 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
  • G10L21/0216—Noise filtering characterised by the method used for estimating noise
  • G10L21/0232—Processing in the frequency domain
• • 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
  • G10L21/0272—Voice signal separating
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS
  • H04R3/00—Circuits for transducers
  • H04R3/04—Circuits for transducers for correcting frequency response
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04R—LOUDSPEAKERS, MICROPHONES, GRAMOPHONE PICK-UPS OR LIKE ACOUSTIC ELECTROMECHANICAL TRANSDUCERS; ELECTRIC HEARING AIDS; PUBLIC ADDRESS SYSTEMS
  • H04R5/00—Stereophonic arrangements
  • H04R5/04—Circuit arrangements, e.g. for selective connection of amplifier inputs/outputs to loudspeakers, for loudspeaker detection, or for adaptation of settings to personal preferences or hearing impairments
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S3/00—Systems employing more than two channels, e.g. quadraphonic
  • H04S3/008—Systems employing more than two channels, e.g. quadraphonic in which the audio signals are in digital form, i.e. employing more than two discrete digital channels
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S3/00—Systems employing more than two channels, e.g. quadraphonic
  • H04S3/02—Systems employing more than two channels, e.g. quadraphonic of the matrix type, i.e. in which input signals are combined algebraically, e.g. after having been phase shifted with respect to each other
• • 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
  • G10L21/0216—Noise filtering characterised by the method used for estimating noise
  • G10L2021/02161—Number of inputs available containing the signal or the noise to be suppressed
  • G10L2021/02163—Only one microphone
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04S—STEREOPHONIC SYSTEMS 
  • H04S2420/00—Techniques used stereophonic systems covered by H04S but not provided for in its groups
  • H04S2420/11—Application of ambisonics in stereophonic audio systems

Definitions

• the present invention relates to the field of audio or acoustic signal processing, and more particularly to the processing of real multichannel sound content in ambiophonic format (or "ambisonic” hereinafter).
• the ambisonic technique consists in exploiting in each frequency band a subset of channels that have desired directivity characteristics. As an example of application, mention may be made of:
• the ambisonie consists of a projection of the acoustic field on a basis of spherical harmonic functions (base illustrated in FIG. 1), to obtain a spatialized representation of the sound scene.
• the function Y n ( ⁇ , ⁇ ) is the spherical harmonic of order m and index ⁇ , depending on the spherical coordinates ( ⁇ , ⁇ ), defined with the following formula:
• a real ambisonic encoding is made from a network of sensors, generally distributed over a sphere, which are combined to synthesize an ambisonic content whose channels respect at best the directivities of the spherical harmonics (as illustrated in FIG. ).
• a microphone MIC comprises a plurality of piezoelectric capsules C1, C2,... Which receive sound waves in different directions of arrival of the space.
• a UT processing unit receiving the signals from these capsules performs an ambisonic encoding using a filter matrix presented below, and delivers ambisonic signals (formalized in a spherical harmonic base of the type illustrated in FIG. figure 1).
• Ambisonic formalism initially limited to the representation of spherical harmonic functions of order 1, was later extended to higher orders.
• Ambisonic formalism with a larger number of components is commonly referred to as “Higher Order Ambisonics” (or “HOA” hereinafter).
• a content of order M contains a total of (M + 1) 2 channels (4 channels at order 1, 9 channels at order 2, 16 channels to order 3, and so on).
• ambisonic components is understood to mean the ambisonic signal in each ambisonic channel, with reference to the “vector components” in a vector base that would be formed by each spherical harmonic function. For example, we can count:
• A is a matrix called "mixing matrix", of dimensions (M + 1) 2 ⁇ N and of which each column A contains the mixing coefficients of the source / ' .
• this matrix A corresponds to the encoding coefficients of each source, associated with each direction of each source / ' .
• a matrix B called "separation matrix", inverse of the matrix A.
• ACI independent component analysis algorithm
• This step is to make the formation of ways (or "beamforming” below), that is to say to combine different channels with different directivities, to create a new component with the desired directivity.
• ways or "beamforming” below
• the decoding matrix B is formulated here from the positions of the loudspeakers of a sound reproduction system and the signals intended for the loudspeakers are extracted according to the same method as that used for the source separation.
• the sensors used have physical limitations that lead to a degradation of the microphone encoding, and therefore a degradation of the directivity of the ambison components.
• high frequency encoding degrades when the inter-sensor spacing becomes approximately half a wavelength: this is due to the spatial folding phenomenon.
• the microphone capsules tend to become omnidirectional and it becomes impossible to obtain the desired directivities.
• the degradation at low frequencies is more marked when it comes to synthesize high order ambison components.
• the associated directivities are more complex and therefore more sensitive to variations in the properties of the sensors.
• Figure 5 illustrates the degree of correlation between theoretical encoding and actual encoding from a 32-capsule spherical microphone, as a function of frequency and ambisonic order.
• Figure 5 shows that the highest degree of correlation is generally achieved for frequencies between 1 kHz and 10 kHz. Nevertheless, for the other frequency ranges (except for the ambisonic orders 0 and 1), the extraction of sources would not always lead to the same result for a theoretical encoding and for a real encoding of these same sources. More specifically, for frequencies outside the range [1 kHz-10 kHz], the extracted components are potentially degraded.
• Figure 6 shows the real directivity in the horizontal plane of the first components of orders 0, 1, 2 and 3 as a function of the sound frequency. It appears in Figure 6 that the actual components are not properly encoded.
• the order 1, 2 and 3 components also have biased directivities for frequencies lower than 10 kHz. More generally, once the theoretical directivity is no longer respected, the beamforming done no longer makes it possible to extract the desired components properly. For example, this results in the appearance of interference during the separation of sources. This can also result in a degradation of the spatial rendering in frequency bands concerned by a multichannel broadcast. More particularly, there is a loss of energy at low frequencies in high orders during encoding. This implies that sources extracted through high order channels may lose some of their energy in the frequencies concerned.
• the present invention improves this situation.
• a processing of the ambisonic decoding matrix for extracting, by matrix size reduction, a plurality of ambisonic decoding sub-matrices each associated with an ambisonic order and with a frequency band chosen for this ambisonic order,
• the decoding matrix is a source separation matrix
• one loudspeaker among several loudspeakers with a well-identified position in the space, and powered in particular by one of the decoded signals mentioned above.
• a frequency band can be defined by several frequency bands or frequency subbands.
• ambisonic decoding sub-matrices for each frequency band, and for each ambisonic order, makes it possible to take advantage in each frequency band of a maximum number of ambison channels that are actually valid in each sub-matrix, so to restore a decoded signal little or no degradation.
• each ambisonic decoding sub-matrix is associated with a frequency band chosen according to a validity criterion of the ambison components of the order with which said sub-matrix is associated, in said selected frequency band.
• Such an embodiment makes it possible to isolate the ambison components constituting each order, in order to process them in the frequency range in which they are valid.
• the criterion of validity of the components may be defined by the conditions for capturing said ambisonic components, by at least one ambisonic microphone.
• the method may further comprise:
• ambisonic microphone data used for ambisonic capture makes it possible to refine the determination of the frequency bands chosen for the elaboration of sub-matrices. Indeed, the ambisonic processing is done on sub-matrices whose ambison components respond strictly to the validity criterion in the associated frequency bands.
• the ambisonic microphone data used for capturing is not always accessible.
• each ambisonic decoding sub-matrix being associated with an ambisonic order and with a frequency band chosen for this ambisonic order, a frequency band can be chosen in a range of 100 Hz to 10 kHz for the ambisonic order.
• a frequency band associated with an ambisonic order may comprise several FFT frequency bands.
• several frequency bands can be associated with an ambisonic order.
• the processing of the ambisonic decoding matrix comprises:
• a treatment of the mixing matrix for extracting, by matrix size reduction, a plurality of mixing sub-matrices each associated with an ambisonic order and a chosen frequency band, and an inversion of the mixing sub-matrices to respectively obtain said ambisonic decoding sub-matrices.
• the ambisonic signal is sufficiently represented in this frequency band 4-6 kHz, as will be seen below.
• the processing of the ambisonic content is conducted for source separation and said decoding matrix is a blind source separation matrix elaborated from the ambison components.
• the separation matrix can be elaborated from the ambison components filtered at a chosen frequency band and preferably in which the number of ambisonic channels valid according to the aforementioned criterion is maximum.
• the channels are retained for performance accuracy at such a high ambisonic order, but also to keep a maximum of channels correctly represented in this frequency band at lower ambison orders.
• mixing sub-matrices are simplified prior to their inversion by reducing a number of columns of each sub-matrix, the remaining columns of the sub-matrices being chosen so as to retain the least correlated signals. after application of the decoding sub-matrices.
• the signal in a reverberant environment, the signal consists of direct fields resulting from the equivalent "free field" propagation of each source and reflections on walls of the acoustic environment.
• mixing sub-matrices are simplified before their inversion, by reducing a number of columns of each sub-matrix, the remaining columns of the sub-matrices being chosen so as to retain signals corresponding to direct sound fields after application of the decoding sub-matrices.
• the above-mentioned decoding matrix may be an inverse matrix of relative spatial positions of the loudspeakers.
• the method comprises in particular, for an ambisonic content broken down into frequency subbands, an application of decoding sub-matrices, obtained by:
• the present invention also relates to a computer program comprising instructions for the implementation of the method when the program is executed by a processor.
• An example of a flowchart of the general algorithm of such a program is illustrated in FIG. 7 commented below, which is specified in FIGS. 8 and 9.
• the present invention also relates to a computing device comprising:
• the present invention thus proposes using channel formation from a real ambisonic encoding by taking advantage, in each frequency band, of all the channels whose directivity respects the ambisonic formalism.
• An embodiment presented above then makes it possible to determine one or more mixing matrices Ak, corresponding to sub-matrices obtained from the theoretical matrix A, and each formulated in a frequency band, then inverted to give matrices. decoding Bk.
• the invention offers a generic treatment of any ambisonic content, including real, possibly affected by physical limitations of a recording system, and without any constraint to limit the total bandwidth of sources extracted .
• FIG. 1 illustrates a base of spherical harmonic functions of order 0 (first line) to 3 (last line), with light gray in positive values and dark gray in negative values;
• FIG. ambisonic encoding from a spherical microphone FIG. 3 illustrates the formation of channels for the extraction of three components, for different ambisonic orders,
• FIG. 4 very schematically illustrates an ambisonic decoding system based on ambisonic components
• FIG. 5 illustrates the correlation between an ideal ambisonic encoding and a real encoding
• FIG. 6 illustrates the directivity in the horizontal plane, measured for a real ambisonic encoding (from left to right successively the components of the orders 0, 1, 2 and 3),
• FIG. 7 illustrates the main steps of an exemplary method within the meaning of the invention
• FIG. 8 illustrates the steps of a particular embodiment of the method according to the invention
• FIG. 9 is a block diagram of a processing algorithm corresponding to the embodiment illustrated in FIG. 7, and
• FIG. 10 schematically illustrates a possible device for the implementation of the invention.
• FIG. 7 The overall scheme of an overall ambisonic processing method in the sense of the invention is presented in FIG. 7. It is for example an ambisonic decoding method.
• ambisonic decoding is understood to mean both the provision of decoded signals, for example intended to supply respective loudspeakers for surround reproduction, and a provision, more generally, of signals each associated with a sound source. especially in the source separation technique.
• An ambisonic microphone is a microphone composed of a plurality of microphonic capsules generally distributed spherically and as regularly as possible. These capsules act as sound signal sensors. The microphone capsules are arranged on the ambisonic microphone so as to pick up sound signals according to their directivity in the space. As illustrated in FIG.
• Stage S2 therefore aims to recover the data characterizing the ambisonic microphone PCM (and possibly the conditions for capturing the ambisonic content c (t), and / or the reverberation conditions during capture, or other).
• a characterizing feature of the ambisonic microphone MIC may be the inter-capsule spacing. Indeed, the encoding of high frequencies is degraded when the inter-sensor spacing becomes greater than half a wavelength. This is due to the phenomenon of aliasing. Conversely, for a low frequency signal, too close microphonic capsules can not generate the desired directivity.
• a BFA analysis filter bank may be applied to the ambisonic content x (t) in order subsequently to select, in step S31, signals of filtered ambison components in frequency ranges in which the representation ambisonic for a given order m is the most exact (thus respecting a "validity criterion" of the ambisonic representation), and this according to the data of the microphone defined above.
• the step S4 aims at obtaining a matrix decoding B, depending on the type of treatment chosen.
• the decoding matrix B is the inverse of a matrix A containing coefficients specific to spatial positions of loudspeakers used for the restitution.
• the decoding matrix B is initially generated in step S4 for blind source separation processing from filtered and selected ambison components. More particularly, this decoding matrix B is elaborated for the frequency band containing the largest number of valid ambison channels (and the largest possible order M).
• the determination of the validity frequency bands of the different ambisonic orders can be adapted to the ambisonic microphone used to capture the ambisonic components to be decoded. To do this, it is possible, for example, to rely on the frequency variations of the accuracy of the ambisonic representation for different orders m, of the type illustrated in FIG.
• step S7 at least two matrices B1, B2 are determined, resulting from a matrix reduction of the decoding matrix B for each sub-frequency band (in the example illustrated, the frequency sub-bands f1 and f2 ).
• a matrix reduction of the decoding matrix B for each sub-frequency band in the example illustrated, the frequency sub-bands f1 and f2 .
• step S8 the product of each matrix B1 and B2 obtained in the preceding step is carried out by filtered ambison signals. in the corresponding sub-bands f1, f2.
• FIG. 8 illustrates the steps of a particular embodiment of the method according to the invention. More precisely, FIG. 8 presents process steps that can be implemented between steps S4 and S7 of FIG. 7.
• step S4 as described above, the decoding matrix B defined above is obtained.
• step S5 it is possible to invert this decoding matrix B (or equivalently, a determination of its pseudo-inverse) in order to obtain the corresponding mixing matrix A (step S51).
• the mixing matrix A can thus contain coefficients relating to respective positions of sound sources to be extracted.
• the mixing matrix A may contain coefficients relating to the position of the speakers on which it is desired to restore the decoded signals.
• step S6 it is possible to reduce the dimensions of the mixing matrix A to obtain sub-matrices A1, A2. It is a matrix reduction whose number of lines corresponds to the number of ambisonic channels for each order.
• each mixing sub-matrix thus obtained is of dimension N x Ntarget, with Ntarget the number of sources resulting from the blind source separation or the number of loudspeakers provided for a restitution.
• the number of speakers is preferably equal to or greater than the number of lines.
• the number of columns may be less than or equal to the number of rows.
• columns can be deleted and for example kept sources whose signals are of higher energies and / or those which are the least correlated (sources that are the least "mixed" possible). and / or the signals correspond to the direct field of the sources, or others.
• step S71 an inversion of each mixing sub-matrix A1, A2 is performed in order to obtain respectively the decoding sub-matrices B1, B2 presented above (step S7).
• the passage through the mixing matrix A makes it possible in particular to maintain satisfactory levels of energy of the ambison components associated with each order, despite the matrix reductions.
• the steps S5 to S71 make it possible to "refine" the decoding of the ambisonic content x (t).
• FIG. 9 is a block diagram of a processing algorithm corresponding to the embodiment illustrated in FIGS. 7 and 8.
• the same step references S1, S2, etc. have been used to designate identical or similar steps. and presented above with reference to FIGS. 7 and 8.
• "Ambisonic" and "source” microphone signals are called “channels” for the signals to be extracted (sources actually to be extracted or the signals for powering the loudspeakers).
• step S2 data relating to the ambisonic capture of the content x (t) is available (data relating to the ambisonic microphone MIC used, etc.).
• a frequency band is determined for each ambisonic order.
• a filter bank for reconstruction is applied to the N ambisonic channels in step S3 to give K subbands denoted xk.
• the sub-bands are chosen to correspond to the different validity ranges of the microphone encoding.
• a source separation matrix B is used which is elaborated according to the frequency-filtered ambison components. (top arrow coming on rectangle S4A). More particularly, a method for the blind separation of sources is applied in the sub-band containing the most valid channels, to obtain a separation matrix B of dimensions Ntarget ⁇ N, where Ntarget is the number of sources obtained by the blind separation method. in the selected frequency sub-band.
• the valid channels are determined from a validity criterion relative to each order of the ambisonic content x (t) as a function of each frequency band of the filterbank. More generally, in order to maximize the quality of the source separation, a frequency band comprising the most valid ambison components is chosen.
• Valid means components whose energy criteria or directivity have not been skewed during ambisonic capture, as presented above with reference to Figure 5.
• the validity of each order in frequency bands of the The audio domain can be established by knowing the limits of the ambisonic microphone used when capturing the ambisonic content x (t), or by using an abacus established on the basis of measurements made on a plurality of ambisonic microphones, allowing to average the validity of each ambisonic order in each frequency band.
• first-order ambison channels tend to be valid in a frequency range from 100HZ to about 10kHz.
• the frequency band in which the second-order ambisonic channels may be more generally valid may for example be from 1 kHz to 9 kHz, etc.
• the decoding matrix is constructed according to the position of the speakers on which the content is to be reproduced. More exactly, this decoding matrix B corresponds to the inverse of a mixing matrix A which is defined by the respective spatial positions of the loudspeakers.
• the "theoretical" mixing matrix A (for the two aforementioned variants) is constructed by inverting B.
• the mixing matrix is composed of N rows and Ntarget columns, the ith column containing the spherical harmonic coefficients, relative to the coordinates (0 ;, ⁇ ;) of the source s ,.
• a mixing matrix A in the case of a source separation for a second-order ambisonic content consisting of five sources: s, s
• A is composed of N lines and a minimum of N columns, the ith column containing the spherical harmonic coefficients relative to the coordinates (0 ;, ⁇ ;) of the loudspeaker i.
• a mixing sub-matrix Ak is constructed, such that Ak is a truncated version of the matrix A, retaining only the Nk lines corresponding to the actually valid channels in this subband k.
• Nk is smaller than the number of Ntarget sources sought in the subband, only one set of Ntarget is retained, k, columns (with Ntarget, k less than or equal to Nk), chosen according to energy criteria (for example by separating the sources having the greatest contribution) or according to other criteria of interest as defined above.
• step S7 the matrix Ak is inverted to give Bk.
• the submatrix Ak is not a square matrix, infinite possibilities exist for the inversion.
• a pseudo-inversion can be applied, or an inversion by applying additional constraints (for example choice of the solution giving the most directional beamforming, or minimizing the side lobes).
• matrix inversion is understood to mean both a conventional inversion of the matrix and a pseudo-inversion as presented above.
• ambisonic content of order 2 (9 channels) sampled at 16kHz, denoted x (t) consisting of 3 sources that we want to extract.
• Ambisonic encoding at orders 0 and 1 is valid between 200Hz and 8000Hz.
• the encoding of order 2 is valid between 900Hz and 8000Hz.
• a filter bank is implemented, consisting of two frequency bands, 200Hz-900Hz (up to order 1) and 900Hz-8000Hz (use of order 2)
• xl (t) consists of 4 channels (ambisonie of order 1) and x2 (t) contains 9 channels (ambisonie of order 2).
• a separation matrix B of dimensions 3 ⁇ 9 is estimated by independent component analysis carried out in the 900 Hz-8000 Hz sub-band, that is to say x 2 (t).
• a theoretical mixing matrix A of dimensions 9 ⁇ 3, is deduced by inversion of B, each column i containing the spherical harmonic coefficients of the source i.
• the matrices Al and A2 are calculated from A to extract the sources in each subband:
• the present invention is further directed to a DIS device for implementing the invention.
• This device DIS may comprise an input interface IN for receiving ambisonic signals x (t).
• the device DIS may comprise a memory MEM for storing instructions of a computer program within the meaning of the invention.
• the computer program instructions are ambisonic signal processing instructions x (t). They are implemented by a processor P OC, in order to deliver, via an output interface OUT, decoded signals s (t).
• the frequency ranges for which the ambisonic representation is valid are given above by way of example and may differ depending on the nature of the ambisonic microphones used for capturing, or even the capture conditions themselves.

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