Abstract: There are two representations for Higher Order Ambisonics denoted HOA: spatial domain and coefficient domain. The invention generates from a coefficient domain representation a mixed spatial/coefficient domain representation, wherein the number of said HOA signals can be variable. A vector of coefficient domain signals is separated into a vector of coefficient domain signals having a constant number of HOA coefficients and a vector of coefficient domain signals having a variable number of HOA coefficients. The constant-number HOA coefficients vector is transformed to a corresponding spatial domain signal vector. In order to facilitate high-quality coding, without creating signal discontinuities the variable-number HOA coefficients vector of coefficient domain signals is adaptively normalised and multiplexed with the vector of spatial domain signals.

Abstract: A method, a computer readable medium, and an apparatus for multichannel audio playback adaptation. A user input defining a listening region relative to a loudspeaker arrangement is received via an input. A distance calculating unit determines minimal distances between the listening region and the loudspeakers. A comparator compares the determined minimal distances with a critical distance. A parameter setting unit then adapts output parameters for those loudspeakers for which the determined minimal distance is below the critical distance.

Abstract: A method, a computer readable storage medium, and an apparatus for determining a target sound scene at a target position from two or more source sound scenes. A positioning unit positions spatial domain representations of the two or more source sound scenes in a virtual scene. These representations are represented by virtual loudspeaker positions. A projecting unit then obtains projected virtual loudspeaker positions of a spatial domain representation of the target sound scene by projecting the virtual loudspeaker positions of the two or more source sound scenes on a circle or a sphere around the target position.

Abstract: For an efficient encoding of subband configuration data the first, penultimate and last subband groups are treated differently than the other subband groups. Further, subband group bandwidth difference values are used in the encoding. The number of subband groups NSB is coded using a fixed number of bits representing NSB?1. The bandwidth value BSB[1] of the first subband group is coded using a unary code representing BSB[1]?1. No bandwidth value BSB[g] is coded for the last subband g=NSB. For subband groups g=2, . . . , NSB?2 bandwidth difference values ?BSB [g]=BSB [g]?BSB[g?1] are coded using a unary code, and the bandwidth difference value ?BSB[NSB?1] for subband group g=NSB?1 is coded using a fixed number of bits.

Abstract: The invention is suited for improving a low bit rate compressed and decompressed Higher Order Ambisonics HOA signal representation of a sound field, wherein the decompression provides a spatially sparse decoded HOA representation and a set of indices of coefficient sequences of this representation. From reconstructed signals of the original HOA representation a number of modified phase spectra signals are created using de-correlation filters, which modified phase spectra signals are uncorrelated with the signals of said original representation. The modified phase spectra signals are mixed with each other using predetermined mixing parameters, in order to provide a replicated ambient HOA component. Finally the spatially sparse decoded HOA representation is enhanced with the replicated time domain HOA representation.

Abstract: Higher Order Ambisonics represents three-dimensional sound independent of a specific loudspeaker set-up. However, transmission of an HOA representation results in a very high bit rate. Therefore compression with a fixed number of channels is used, in which directional and ambient signal components are processed differently. The ambient HOA component is represented by a minimum number of HOA coefficient sequences. The remaining channels contain either directional signals or additional coefficient sequences of the ambient HOA component, depending on what will result in optimum perceptual quality. This processing can change on a frame-by-frame basis.

Abstract: The invention improves HOA sound field representation compression. The HOA representation is analysed for the presence of dominant sound sources and their directions are estimated. Then the HOA representation is decomposed into a number of dominant directional signals and a residual component. This residual component is transformed into the discrete spatial domain in order to obtain general plane wave functions at uniform sampling directions, which are predicted from the dominant directional signals. Finally, the prediction error is transformed back to the HOA domain and represents the residual ambient HOA component for which an order reduction is performed, followed by perceptual encoding of the dominant directional signals and the residual component.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component (CAMB(k?1)). The ambient HOA component (CAMB(k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (CAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component ({tilde over (C)}AMB (k?1)). The ambient HOA component ({tilde over (C)}AMB (k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (cAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates.

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. A method for low bit-rate encoding frames of an input HOA signal having coefficient sequences comprises computing (s110) a truncated HOA representation (CT(k)), determining (s111) active coefficient sequences (1c,Act(k)), estimating (s16) candidate directions (MDIR(k)), dividing (s15) the input HOA signal into a plurality of frequency subbands (f1, . . . , fF), estimating (s161) for each of the frequency subbands a subset of candidate directions (MDIR(k)) as active directions (MDIR(k,f1), . . . , MDIR(k,fF)) and for each active direction a trajectory, computing (s17) for each frequency subband directional subband signals from the coefficient sequences of the frequency subband according to the active directions, calculating (s18) for each frequency subband a prediction matrix (A(k,f1), . . .

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. A method for low bit-rate encoding frames of an input HOA signal having coefficient sequences comprises computing (s110) a truncated HOA representation (CT(k)), determining (s111) active coefficient sequences (IC,ACTT(k)), estimating (s16) candidate directions (MDIR(k)), dividing (s15) the input HOA signal into a plurality of frequency subbands (f1, . . . , fF), estimating (s161) for each of the frequency subbands a subset of candidate directions (MDIR(k)) as active directions (MDIR(k,f1), . . . , MDIR(k,fF)) and for each active direction a trajectory, computing (s17) for each frequency subband directional subband signals from the coefficient sequences of the frequency subband according to the active directions, calculating (s18) for each frequency subband a prediction matrix (A(k,f1), . . .

Abstract: Encoding of Higher Order Ambisonics (HOA) signals commonly results in high data rates. For data rate reduction, a method (100) for encoding direction information for frames of an input HOA signal comprises determining (s101) active candidate directions (MDIR(k)) among predefined global directions having global direction indices, dividing (s102) the input HOA signal into frequency subbands (f1 . . .

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number {? e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: There are two representations for Higher Order Ambisonics denoted HOA: spatial domain and coefficient domain. The invention generates from a coefficient domain representation a mixed spatial/coefficient domain representation, wherein the number of said HOA signals can be variable. A vector of coefficient domain signals is separated into a vector of coefficient domain signals having a constant number of HOA coefficients and a vector of coefficient domain signals having a variable number of HOA coefficients. The constant-number HOA coefficients vector is transformed to a corresponding spatial domain signal vector. In order to facilitate high-quality coding, without creating signal discontinuities the variable-number HOA coefficients vector of coefficient domain signals is adaptively normalized and multiplexed with the vector of spatial domain signals.

Abstract: A method for compressing a HOA signal being an input HOA representation with input time frames (C(k)) of HOA coefficient sequences comprises spatial HOA encoding of the input time frames and subsequent perceptual encoding and source encoding. Each input time frame is decomposed (802) into a frame of predominant sound signals (XPS(k?1)) and a frame of an ambient HOA component (CAMB(k?1)). The ambient HOA component (C˜AMB(k?1)) comprises, in a layered mode, first HOA coefficient sequences of the input HOA representation (cn(k?1)) in lower positions and second HOA coefficient sequences (cAMB,n(k?1)) in remaining higher positions. The second HOA coefficient sequences are part of an HOA representation of a residual between the input HOA representation and the HOA representation of the predominant sound signals.

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to (AA).

Abstract: When compressing an HOA data frame representation, a gain control (15, 151) is applied for each channel signal before it is perceptually encoded (16). The gain values are transferred in a differential manner as side information. However, for starting decoding of such streamed compressed HOA data frame representation absolute gain values are required, which should be coded with a minimum number of bits. For determining such lowest integer number (?e) of bits the HOA data frame representation (C(k)) is rendered in spatial domain to virtual loudspeaker signals lying on a unit sphere, followed by normalisation of the HOA data frame representation (C(k)). Then the lowest integer number of bits is set to: (AA).

Abstract: The invention improves HOA sound field representation compression. The HOA representation is analyzed for the presence of dominant sound sources and their directions are estimated. Then the HOA representation is decomposed into a number of dominant directional signals and a residual component. This residual component is transformed into the discrete spatial domain in order to obtain general plane wave functions at uniform sampling directions, which are predicted from the dominant directional signals. Finally, the prediction error is transformed back to the HOA domain and represents the residual ambient HOA component for which an order reduction is performed, followed by perceptual encoding of the dominant directional signals and the residual component.