WO2014090660A1 - Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field - Google Patents

Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field Download PDF

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Publication number
WO2014090660A1
WO2014090660A1 PCT/EP2013/075559 EP2013075559W WO2014090660A1 WO 2014090660 A1 WO2014090660 A1 WO 2014090660A1 EP 2013075559 W EP2013075559 W EP 2013075559W WO 2014090660 A1 WO2014090660 A1 WO 2014090660A1
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Prior art keywords
hoa
signals
dir
residual
order
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English (en)
French (fr)
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Alexander Krueger
Sven Kordon
Johannes Boehm
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Thomson Licensing SAS
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Thomson Licensing SAS
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Priority to EP13801563.1A priority Critical patent/EP2932502B1/en
Priority to CN201910024905.5A priority patent/CN109616130B/zh
Priority to EP21209477.5A priority patent/EP3996090B1/en
Priority to KR1020247014936A priority patent/KR20240068780A/ko
Priority to CN201380064856.9A priority patent/CN104854655B/zh
Priority to KR1020157015332A priority patent/KR102202973B1/ko
Priority to MX2017000541A priority patent/MX395017B/es
Priority to MX2015007349A priority patent/MX344988B/es
Priority to EP25152324.7A priority patent/EP4553829A1/en
Priority to KR1020237020580A priority patent/KR102664626B1/ko
Priority to EP18196348.9A priority patent/EP3496096B1/en
Priority to CN202311300470.5A priority patent/CN117392989A/zh
Priority to CN201910024906.XA priority patent/CN109545235B/zh
Priority to KR1020217000640A priority patent/KR102428842B1/ko
Priority to US14/651,313 priority patent/US9646618B2/en
Priority to CN202310889802.1A priority patent/CN117037813A/zh
Priority to KR1020227026512A priority patent/KR102546541B1/ko
Application filed by Thomson Licensing SAS filed Critical Thomson Licensing SAS
Priority to JP2015546945A priority patent/JP6285458B2/ja
Priority to RU2015128090A priority patent/RU2623886C2/ru
Priority to CN201910024894.0A priority patent/CN109410965B/zh
Priority to HK16104077.0A priority patent/HK1216356B/en
Priority to CN201910024895.5A priority patent/CN109448742B/zh
Priority to CN202310889797.4A priority patent/CN117037812A/zh
Priority to CA2891636A priority patent/CA2891636C/en
Publication of WO2014090660A1 publication Critical patent/WO2014090660A1/en
Anticipated expiration legal-status Critical
Priority to US15/435,175 priority patent/US10038965B2/en
Priority to US16/019,256 priority patent/US10257635B2/en
Priority to MYPI2018704146A priority patent/MY191376A/en
Priority to US16/276,363 priority patent/US10609501B2/en
Priority to US16/828,961 priority patent/US11184730B2/en
Priority to US17/532,246 priority patent/US11546712B2/en
Priority to US18/068,096 priority patent/US12425791B2/en
Ceased legal-status Critical Current

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Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04SSTEREOPHONIC SYSTEMS 
    • H04S7/00Indicating arrangements; Control arrangements, e.g. balance control
    • H04S7/30Control circuits for electronic adaptation of the sound field
    • H04S7/302Electronic adaptation of stereophonic sound system to listener position or orientation
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00Speech 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
    • G10L19/008Multichannel audio signal coding or decoding using interchannel correlation to reduce redundancy, e.g. joint-stereo, intensity-coding or matrixing
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04SSTEREOPHONIC SYSTEMS 
    • H04S3/00Systems employing more than two channels, e.g. quadraphonic
    • H04S3/008Systems 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04HBROADCAST COMMUNICATION
    • H04H20/00Arrangements for broadcast or for distribution combined with broadcast
    • H04H20/86Arrangements characterised by the broadcast information itself
    • H04H20/88Stereophonic broadcast systems
    • H04H20/89Stereophonic broadcast systems using three or more audio channels, e.g. triphonic or quadraphonic
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04SSTEREOPHONIC SYSTEMS 
    • H04S2400/00Details of stereophonic systems covered by H04S but not provided for in its groups
    • H04S2400/01Multi-channel, i.e. more than two input channels, sound reproduction with two speakers wherein the multi-channel information is substantially preserved
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04SSTEREOPHONIC SYSTEMS 
    • H04S2420/00Techniques used stereophonic systems covered by H04S but not provided for in its groups
    • H04S2420/11Application of ambisonics in stereophonic audio systems

Definitions

  • the invention relates to a method and to an apparatus for compressing and decompressing a Higher Order Ambisonics representation for a sound field.
  • HOA Higher Order Ambisonics denoted HOA offers one way of repre ⁇ senting three-dimensional sound.
  • Other techniques are wave field synthesis (WFS) or channel based methods like 22.2.
  • WFS wave field synthesis
  • the HOA representation offers the advantage of being independent of a specific loudspeaker set-up. This flexibility, however, is at the ex ⁇ fie of a decoding process which is required for the play ⁇ back of the HOA representation on a particular loudspeaker set-up.
  • HOA may also be rendered to set-ups consisting of only few loudspeakers.
  • a further advantage of HOA is that the same representation can also be employed without any modification for binaural ren ⁇ dering to head-phones.
  • HOA is based on a representation of the spatial density of complex harmonic plane wave amplitudes by a truncated Spher ⁇ ical Harmonics (SH) expansion.
  • SH Spher ⁇ ical Harmonics
  • Each expansion coefficient is a function of angular frequency, which can be equivalently represented by a time domain function.
  • the complete HOA sound field representation actually can be assumed to consist of 0 time domain func ⁇ tions, where 0 denotes the number of expansion coefficients.
  • These time domain functions will be equivalently referred to as HOA coefficient sequences in the following.
  • the spatial resolution of the HOA representation improves with a growing maximum order N of the expansion.
  • the total bit rate for the transmis ⁇ sion of HOA representation given a desired single-channel sampling rate f $ and the number of bits per sample, is de- termined by 0 ⁇ f s ⁇ .
  • the reconstructed playback signals are usually obtained by a weighted sum of the HOA coefficient sequences, and there is a high probability for unmasking of perceptual coding noise when the decompressed HOA representation is rendered on a particular loudspeaker set-up.
  • the major prob- lem for perceptual coding noise unmasking is high cross correlations between the individual HOA coefficient sequences. Since the coding noise signals in the individual HOA coeffi ⁇ cient sequences are usually uncorrelated with each other, there may occur a constructive superposition of the percep ⁇ tual coding noise while at the same time the noise-free HOA coefficient sequences are cancelled at superposition. A fur ⁇ ther problem is that these cross correlations lead to a re ⁇ cuted efficiency of the perceptual coders.
  • discrete spa ⁇ tial domain is the time domain equivalent of the spatial density of complex harmonic plane wave amplitudes, sampled at some discrete directions.
  • the discrete spatial domain is thus represented by 0 conventional time domain signals, which can be interpreted as general plane waves impinging from the sampling directions and would correspond to the loudspeaker signals, if the loudspeakers were positioned in exactly the same directions as those assumed for the spatial domain transform.
  • Such general plane waves of order lower than N can result from artistic creation in order to make sound sources appearing wider, and can also occur with the recording of HOA sound field representations by spherical microphones.
  • the sound field is represented by a high number of highly correlated spatial domain signals (see also section Spatial resolution of Higher Order Ambi- sonics for an explanation) .
  • a problem to be solved by the invention is to remove the disadvantages resulting from the processing described in pa ⁇ tent application EP 2665208 Al, thereby also avoiding the above described disadvantages of the other cited prior art.
  • This problem is solved by the methods disclosed in claims 1 and 3.
  • Corresponding apparatuses which utilise these methods are disclosed in claims 2 and 4.
  • the invention improves the HOA sound field representation compression processing described in patent application EP 2665208 Al.
  • the HOA represen ⁇ tation is analysed for the presence of dominant sound sources, of which the directions are estimated. With the knowledge of the dominant sound source directions, the HOA representation is decomposed into a number of dominant di ⁇ rectional signals, representing general plane waves, and a residual component.
  • this residual HOA component instead of immediately reducing the order of this residual HOA component, it is transformed into the discrete spatial domain in order to obtain the gen ⁇ eral plane wave functions at uniform sampling directions representing the residual HOA component. Thereafter these plane wave functions are predicted from the dominant direc ⁇ tional signals. The reason for this operation is that parts of the residual HOA component may be highly correlated with the dominant directional signals.
  • That prediction can be a simple one so as to produce only a small amount of side information.
  • the prediction consists of an appropriate scaling and delay.
  • Fi- nally the prediction error is transformed back to the HOA domain and is regarded as the residual ambient HOA component for which an order reduction is performed.
  • the effect of subtracting the predictable signals from the residual HOA component is to reduce its to- tal power as well as the remaining amount of dominant direc ⁇ tional signals and, in this way, to reduce the decomposition error resulting from the order reduction.
  • the inventive compression method is suited for compressing a Higher Order Ambisonics representation denoted HOA for a sound field, said method including the steps:
  • the inventive compression apparatus is suited for compressing a Higher Order Ambisonics representation de noted HOA for a sound field, said apparatus including:
  • means being adapted for estimating dominant sound source directions from a current time frame of HOA coefficients; means being adapted for decomposing, depending on said HOA coefficients and on said dominant sound source direc ⁇ tions, said HOA representation into dominant directional signals in time domain and a residual HOA component, wherein said residual HOA component is transformed into the discrete spatial domain in order to obtain plane wave functions at uniform sampling directions representing said residual HOA component, and wherein said plane wave functions are pre ⁇ dicted from said dominant directional signals, thereby providing parameters describing said prediction, and the corresponding prediction error is transformed back into the HOA domain;
  • means being adapted for perceptually encoding said domi ⁇ nant directional signals and said residual HOA component time domain signals so as to provide compressed dominant di ⁇ rectional signals and compressed residual component signals.
  • the inventive decompression method is suited for decompressing a Higher Order Ambisonics representation compressed according to the above compression method, said decompressing method including the steps:
  • the inventive decompression apparatus is suited for decompressing a Higher Order Ambisonics representation compressed according to the above compressing method, said decompression apparatus including:
  • Fig. la compression step 1 decomposition of HOA signal into a number of dominant directional signals, a residual ambient HOA component and side information;
  • Fig. lb compression step 2 order reduction and decorrela- tion for ambient HOA component and perceptual encod- ing of both components;
  • Fig. 2a decompression step 1 perceptual decoding of time domain signals, re-correlation of signals represent ⁇ ing the residual ambient HOA component and order ex ⁇ tension;
  • Fig. 2b decompression step 2 composition of total HOA representation
  • the compression processing according to the invention includes two successive steps illustrated in Fig. la and Fig. lb, respectively.
  • the exact definitions of the individual signals are described in section Detailed description of HOA decomposition and recomposition .
  • a frame-wise processing for the compression with non-overlapping input frames D(k) of HOA coefficient sequences of length B is used, where k denotes the frame index.
  • the frames are defined with respect to the HOA coefficient sequences specified in equation (42) as
  • D(k): [d((kB + 1)T S ) d((kB + 2)T S ) ... d((kB + B)T S ) ], (1) where T s denotes the sampling period.
  • a frame D(k) of HOA coefficient sequences is in ⁇ put to a dominant sound source directions estimation step or stage 11, which analyses the HOA representation for the presence of dominant directional signals, of which the di ⁇ rections are estimated.
  • the direction estimation can be per ⁇ formed e.g. by the processing described in patent applica ⁇ tion EP 2665208 Al .
  • the direction estimates are appropriately ordered by assigning them to the direction es ⁇ timates from previous frames.
  • the temporal sequence of an individual direction estimate is assumed to describe the directional trajectory of a dominant sound source.
  • the d-th dominant sound source is supposed not to be active, it is possible to indicate this by assign ⁇ ing a non-valid value to ⁇ DOM .
  • the HOA representation is decomposed in a decomposing step or stage 12 into a number of maximum T) dominant directional signals X mR (k— 1), some pa ⁇ rameters (/c— 1) describing the prediction of the spatial domain signals of the residual HOA component from the dominant directional signals, and an ambient HOA component D A (k— 2) representing the prediction error.
  • T maximum T
  • X mR k— 1
  • pa ⁇ rameters describing the prediction of the spatial domain signals of the residual HOA component from the dominant directional signals
  • D A ambient HOA component
  • Fig. lb the perceptual coding of the directional signals X mR (k— 1) and of the residual ambient HOA component D A (k— 2), is shown.
  • the directional signals X mR (k— 1) are conventional time domain signals which can be individually compressed us ⁇ ing any existing perceptual compression technique.
  • the com- pression of the ambient HOA domain component D A (k— 2) is carried out in two successive steps or stages.
  • Such order reduction is accomplished by keeping in D A (k— 2) only N REO HOA coefficients and dropping the other ones.
  • the reduced order N REO may in general be chosen smaller, since the total power as well as the re ⁇ maining amount of directivity of the residual ambient HOA component is smaller. Therefore the order reduction causes smaller errors as compared to EP 2665208 Al .
  • the HOA coefficient sequences representing the order reduced ambient HOA component D AREO (k— 2) are decorrelated to obtain the time do ⁇ main signals W ARED (/c— 2) , which are input to (a bank of) par- allel perceptual encoders or compressors 15 operating by any known perceptual compression technique.
  • the decorrelation is performed in order to avoid perceptual coding noise unmask ⁇ ing when rendering the HOA representation following its decompression (see patent application EP 12305860.4 for expla- nation) .
  • An approximate decorrelation can be achieved by transforming D ARED (k— 2) to O RED equivalent signals in the spatial domain by applying a Spherical Harmonic Transform as described in EP 2469742 A2.
  • an adaptive Spherical Harmonic Transform as proposed in patent application EP 12305861.2 can be used, where the grid of sampling directions is rotated to achieve the best possible decorrelation effect.
  • a further alterna ⁇ tive decorrelation technique is the Karhunen-Loeve transform (KLT) described in patent application EP 12305860.4. It is noted that for the last two types of de-correlation some kind of side information, denoted by a(k— 2), is to be pro ⁇ vided in order to enable reversion of the decorrelation at a HOA decompression stage.
  • the perceptual compression of all time domain signals X mR (k— 1) and W ARED (/c— 2) is performed jointly in order to improve the coding efficiency.
  • Output of the perceptual coding is the compressed direction- al signals X mR (k— 1) and the compressed ambient time domain signals W AREO (k— 2) .
  • Fig. 2a The decompression processing is shown in Fig. 2a and Fig. 2b. Like the compression, it consists of two successive steps.
  • Fig. 2a a perceptual decompression of the direc ⁇ tional signals X mR (k— 1) and the time domain signals
  • W ARED (k— 2) representing the residual ambient HOA component is performed in a perceptual decoding or decompressing step or stage 21.
  • the resulting perceptually decompressed time domain signals W ARED (/c— 2) are re-correlated in a re- correlation step or stage 22 in order to provide the residu ⁇ al component HOA representation D AREO (k— 2) of order N RED .
  • the re-correlation can be carried out in a re- verse manner as described for the two alternative process ⁇ ings described for step/stage 14, using the transmitted or stored parameters a(k— 2) depending on the decorrelation method that was used.
  • D ARED (k— 2) an appropriate HOA representation D A (k— 2) of order N is estimated in order extension step or stage 23 by order extension.
  • the order extension is achieved by appending corresponding
  • the total HOA representation is re-composed in a composition step or stage 24 from the decompressed dominant directional signals X mR (k— 1) together with the corresponding directions A ⁇ k and the prediction parameters — 1), as well as from the residual ambient HOA component D A (k— 2), re ⁇ sulting in decompressed and recomposed frame D(k— 2) of HOA coefficients .
  • FIG. 3 A block diagram illustrating the operations performed for the HOA decomposition is given in Fig. 3. The operation is summarised: First, the smoothed dominant directional signals - ⁇ DIR 1) are computed and output for perceptual compression. Next, the residual between the HOA representation Z) DIR (/c— 1) of the dominant directional signals and the original HOA representation D(k— 1) is represented by a number of 0 directional signals -XGRID.DIR 1) r which can be thought of as general plane waves from uniformly distributed directions. These directional signals are predicted from the dominant directional signals X mR (k— 1), where the prediction parame ⁇ ters (/c— 1) are output.
  • the residual D A (k— 2) be ⁇ tween the original HOA representation D(k— 2) and the HOA representation D mR (k— 1) of the dominant directional signals together with the HOA representation ⁇ GRID.DIR 2) of the predicted directional signals from uniformly distributed di ⁇ rections is computed and output.
  • each direction estimate °f an active dominant sound source can be unambiguously specified by a vector containing an inclination angle #DOM,d(k) ⁇ [0> ⁇ ] an d an azimuth angle
  • D ACT (k) denotes the number of active directions for the fc-th frame and d ACTj (k), 1 ⁇ j ⁇ D ACT (k) indicates their indices.
  • STM(-) denotes the real-valued Spherical Har ⁇ monics, which are defined in section Definition of real val ⁇ ued Spherical Harmonics .
  • step or stage 31 the smoothing is explained only for the directional signals DIR (/c), because the smoothing of other types of signals can be accomplished in a completely analogous way.
  • the smoothed directional signals for the (/c— l)-th frame are computed by the appropriate superposition of windowed in ⁇ stantaneous estimates according to
  • a residual HOA representation by directional signals on a uniform grid is calculated in step or stage 33.
  • the purpose of this operation is to obtain directional signals (i.e. general plane wave functions) impinging from some fixed, nearly uniformly distributed directions /2 GRIDo , l ⁇ o ⁇ 0 (also referred to as grid directions), to represent the residual [D(k - 2) D k - 1)] - [D m R (k - 2) D mR (k - 1)] .
  • directional signals on the uniform grid are predicted in step or stage 34.
  • the predic ⁇ tion of the directional signals on the uniform grid composed of the grid directions 2GRID , O > 1 ⁇ o ⁇ 0 from the directional signals is based on two successive frames for smoothing pur ⁇ poses, i.e. the extended frame of grid signals — 1) (of length 2B) is predicted from the extended frame of smoothed dominant directional signals
  • each grid signal GRID.DIR O C ⁇ — 1> / 1 ⁇ o ⁇ 0, contained in — 1) is assigned to a dominant directional signal 3 ⁇ 4iR , EXT ,d — 1) r 1 ⁇ d ⁇ T> , contained in -XDIREXT C ⁇ — 1) .
  • the as ⁇ signment can be based on the computation of the normalised cross-correlation function between the grid signal and all dominant directional signals.
  • that dominant directional signal is assigned to the grid signal, which provides the highest value of the normalised cross-correla ⁇ tion function.
  • the result of the assignment can be formulat- ed by an assignment function ⁇ 1, ... , 0 ⁇ ⁇ 1, ... , £> ⁇ assigning the o-th grid signal to the f /3 ⁇ 4,k -i(°)-th dominant directional signal .
  • each grid signal 3 ⁇ 4RID , DIR , O — 1> is predicted from the assigned dominant directional signal ⁇ , ⁇ ⁇ . ⁇ ) ⁇ — 1> 0 ⁇
  • the prediction error is greater than that of the grid signal itself, the prediction is assumed to have failed. Then, the respective prediction parameters can be set to any non-valid value.
  • All prediction parameters can be arranged in the parameter matrix as
  • the HOA representation of the predicted grid signals is com ⁇ puted in step or stage 35 from -XGRID.DIR C ⁇ — 1) according to
  • ⁇ GRID.DIR C ⁇ — 1) " GRID- ⁇ GRID.DIR C ⁇ — 1) ⁇ (27)
  • ⁇ GRID.DIR C ⁇ — 2) which is a temporally smoothed version (in step/stage 36) of D GRWmR (k— l), from D(k— 2) which is a two-frames delayed version (delays 38 1 and 383 ) of D(k), and from Z) DIR (/c— 2) which is a frame delayed version (delay 382 ) of Z) DIR (/c— 1)
  • the HOA representation of the residual ambient sound field component is computed in step or stage 37 by
  • A(fc-2) (fc-2)- GRIDiDIR (fc-2)- DIR (fc-2) . ( 2 8 )
  • the directional signals — 1) with respect to uni ⁇ formly distributed directions are predicted from the decoded dominant directional signals X mR (k— 1) using the prediction parameters %(k— 1) .
  • the total HOA representation is provided.
  • D(k— 2) is composed from the HOA representation D DIR (k— 2) of the dominant directional signals, the HOA representation
  • Computing HOA representation of dominant directional signals A C) and _Y DIR (fc— 1) are input to a step or stage 4 1 for de ⁇ termining an HOA representation of dominant directional signals.
  • the HOA representation of the dominant directional signals D mK (k— 1) is obtained by
  • D mR (k— 2) i.e. D mR (k— 1) delayed by frame delay 42
  • Z GRIDiDIR (/c— 2) (which is a temporally smoothed version of
  • D(k-2) D mR (k-2) + D GRWiOm (k-2)+D A (k-2) . (35) Basics of Higher Order Ambisonics
  • 5 ⁇ (0,0) denotes the real valued Spherical Harmonics of order n and degree m which are defined in sec ⁇ tion Definition of real valued Spherical Harmonics .
  • the ex ⁇ pansion coefficients ATM(k) are depending only on the angular wave number k . Note that it has been implicitely assumed that sound pressure is spatially band-limited. Thus the se ⁇ ries is truncated with respect to the order index n at an upper limit N, which is called the order of the HOA repre ⁇ sentation .
  • the position index of a time domain function dTM(t) within the vector d(t) is given by n(n + l) + l+m.
  • the final Ambisonics format provides the sampled version of d(t) using a sampling frequency f $ as
  • a general plane wave function x(t) arriving from a direction ⁇ . ⁇ 0 , ⁇ 0 ) ⁇ is represented in HOA by
  • equation (48) it is a product of the general plane wave function x(t) and a spatial dispersion function ⁇ ⁇ ( ⁇ ) , which can be shown to only depend on the angle ⁇ between ⁇ and ⁇ 0 having the property
  • the mode matrix is invertible in gen- eral .
  • the continuous Ambisonics representation can be computed from the directional signals d (t,/2 0 ) by
  • the inventive processing can be carried out by a single processor or elec ⁇ tronic circuit, or by several processors or electronic cir ⁇ cuits operating in parallel and/or operating on different parts of the inventive processing.
  • the invention can be applied for processing corresponding sound signals which can be rendered or played on a loud ⁇ speaker arrangement in a home environment or on a loudspeak ⁇ er arrangement in a cinema.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
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  • Audiology, Speech & Language Pathology (AREA)
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PCT/EP2013/075559 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field Ceased WO2014090660A1 (en)

Priority Applications (31)

Application Number Priority Date Filing Date Title
KR1020227026512A KR102546541B1 (ko) 2012-12-12 2013-12-04 사운드 필드를 위해 고차 앰비소닉스 표현을 압축 및 압축 해제하기 위한 방법 및 장치
EP21209477.5A EP3996090B1 (en) 2012-12-12 2013-12-04 Method and apparatus for decompressing a higher order ambi-sonics representation for a sound field
KR1020247014936A KR20240068780A (ko) 2012-12-12 2013-12-04 사운드 필드를 위해 고차 앰비소닉스 표현을 압축 및 압축 해제하기 위한 방법 및 장치
CN201380064856.9A CN104854655B (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
KR1020157015332A KR102202973B1 (ko) 2012-12-12 2013-12-04 사운드 필드를 위해 고차 앰비소닉스 표현을 압축 및 압축 해제하기 위한 방법 및 장치
MX2017000541A MX395017B (es) 2012-12-12 2013-12-04 Metodo y aparato para comprimir y descomprimir una representacion ambisonica de orden superior para un campo de sonido
MX2015007349A MX344988B (es) 2012-12-12 2013-12-04 Metodo y aparato para comprimir y descomprimir una representacion ambisonica de orden superior para un campo de sonido.
EP25152324.7A EP4553829A1 (en) 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
KR1020237020580A KR102664626B1 (ko) 2012-12-12 2013-12-04 사운드 필드를 위해 고차 앰비소닉스 표현을 압축 및 압축 해제하기 위한 방법 및 장치
EP18196348.9A EP3496096B1 (en) 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
CN202311300470.5A CN117392989A (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
CN201910024906.XA CN109545235B (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
KR1020217000640A KR102428842B1 (ko) 2012-12-12 2013-12-04 사운드 필드를 위해 고차 앰비소닉스 표현을 압축 및 압축 해제하기 위한 방법 및 장치
US14/651,313 US9646618B2 (en) 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a Higher Order Ambisonics representation for a sound field
CN202310889802.1A CN117037813A (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
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CN201910024905.5A CN109616130B (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
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HK16104077.0A HK1216356B (en) 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
CN201910024895.5A CN109448742B (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
CN202310889797.4A CN117037812A (zh) 2012-12-12 2013-12-04 对声场的高阶立体混响表示进行压缩和解压缩的方法和设备
CA2891636A CA2891636C (en) 2012-12-12 2013-12-04 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
US15/435,175 US10038965B2 (en) 2012-12-12 2017-02-16 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
US16/019,256 US10257635B2 (en) 2012-12-12 2018-06-26 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
MYPI2018704146A MY191376A (en) 2012-12-12 2018-11-07 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
US16/276,363 US10609501B2 (en) 2012-12-12 2019-02-14 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
US16/828,961 US11184730B2 (en) 2012-12-12 2020-03-25 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
US17/532,246 US11546712B2 (en) 2012-12-12 2021-11-22 Method and apparatus for compressing and decompressing a higher order ambisonics representation for a sound field
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