Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics (HOA) uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating a panning function (W) using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating a mode matrix (?) from the loudspeaker positions, calculating a pseudo-inverse mode matrix (?+) and decoding the audio soundfield representation. The decoding is based on a decode matrix (D) that is obtained from the panning function (W) and the pseudo-inverse mode matrix (?+).

Abstract: Sound scenes in 3D can be synthesized or captured as a natural sound field. For decoding, a decode matrix is required that is specific for a given loudspeaker setup and is generated using the known loudspeaker positions. However, some source directions are attenuated for 2D loudspeaker setups like e.g. 5.1 surround. An improved method for decoding an encoded audio signal in soundfield format for L loudspeakers at known positions comprises steps of adding (10) a position of at least one virtual loudspeaker to the positions of the L loudspeakers, generating (11) a 3D decode matrix (D?), wherein the positions (Formula I) of the L loudspeakers and the at least one virtual position (Formula II) are used, downmixing (12) the 3D decode matrix (D?), and decoding (14) the encoded audio signal (i14) using the downscaled 3D decode matrix (Formula III). As a result, a plurality of decoded loudspeaker signals (q14) is obtained.

Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics (HOA) uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating (110) a function (W) using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating (120) a mode matrix (?) from the loudspeaker positions, calculating (130) a pseudo-inverse mode matrix (?+) and decoding (140) the audio soundfield representation. The decoding is based on a decode matrix (D) that is obtained from the function (W) and the pseudo-inverse mode matrix (?+).

Abstract: The invention is related to a data structure for Higher Order Ambisonics HOA audio data, which data structure includes 2D or 3D spatial audio content data for one or more different HOA audio data stream descriptions. The HOA audio data can have on order of greater than ‘3’, and the data structure in addition can include single audio signal source data and/or microphone array audio data from fixed or time-varying spatial positions.

Abstract: The invention relates to Higher-Order Ambisonics (HOA) Content Loudness Level Adjustment. A method for adjusting a loudness level of a HOA audio signal on a transmitting side comprises steps of measuring loudness of only the W-channel of the HOA audio signal, and leveling HOA master gain for all channels of the HOA signal according to the measured loudness of the W-channel.

Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics (HOA) uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating (110) a function (W) using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source to directions, calculating (120) a mode matrix (?) from the loudspeaker positions, calculating (130) a pseudo-inverse mode matrix (?+) and decoding (140) the audio soundfield representation. The decoding is based on a decode matrix (D) that is obtained from the function (W) and the pseudo-inverse mode matrix (?+).

Abstract: Soundfield signals as such e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design. A method for improved decoding an audio soundfield representation for audio playback comprises calculating a panning function using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating a mode matrix ? from the loudspeaker positions, calculating a pseudo-inverse mode matrix ?+ and decoding the audio soundfield representation. The decoding is based on a decode matrix that is obtained from the panning function and the pseudo-inverse mode matrix ?+.

Abstract: The invention discloses rendering sound field signals, such as Higher-Order Ambisonics (HOA), for arbitrary loudspeaker setups, where the rendering results in highly improved localization properties and is energy preserving. This is obtained by a new type of decode matrix for sound field data, and a new way to obtain the decode matrix. In a method for rendering an audio sound field representation for arbitrary spatial loudspeaker setups, the decode matrix for the rendering to a given arrangement of target loudspeakers is obtained by steps of obtaining a number of target speakers, their positions, positions of a spherical modeling grid and a HOA order, generating a mix matrix from the positions of the modeling grid and the positions of the speakers, generating a mode matrix from the positions of the spherical modeling grid and the HOA order, calculating a first decode matrix from the mix matrix and the mode matrix, and smoothing and scaling the first decode matrix with smoothing and scaling coefficients.

Abstract: Decoding of Ambisonics representations for a stereo loudspeaker setup is known for first-order Ambisonics audio signals. But such first-order Ambisonics approaches have either high negative side lobes or poor localisation in the frontal region. The invention deals with the processing for stereo decoders for higher-order Ambisonics HOA. The desired panning functions can be derived from a panning law for placement of virtual sources between the loudspeakers. For each loudspeaker a desired panning function for all possible input directions at sampling points is defined. The panning functions are approximated by circular harmonic functions, and with increasing Ambisonics order the desired panning functions are matched with decreasing error. For the frontal region between the loudspeakers, a panning law like the tangent law or vector base amplitude panning (VBAP) are used. For the rear directions panning functions with a slight attenuation of sounds from these directions are defined.

Abstract: The invention is related to a data structure for Higher Order Ambisonics HOA audio data, which data structure includes 2D or 3D spatial audio content data for one or more different HOA audio data stream descriptions. The HOA audio data can have on order of greater than ‘3’, and the data structure in addition can include single audio signal source data and/or microphone array audio data from fixed or time-varying spatial positions.

Abstract: A method and apparatus for approximating a true masking threshold for the quantization of spectral data in an audio transform encoder. According to the invention, for each spectrum to be quantised in the audio signal encoding, an excitation pattern is computed and coded for both long and short window/transform lengths. The excitation patterns are grouped together in a variable-size matrix. A pre-determined sorting order with a fixed number of values only is applied to the excitation pattern data matrix values, and by that re-ordering a quadratic matrix is formed to which matrix' bit planes a SPECK encoding is applied.

Abstract: In lossy based lossless coding a PCM audio signal passes through a lossy encoder to a lossy decoder. The lossy encoder provides a lossy bit stream. The difference signal between the PCM signal and the lossy decoder output is lossless encoded, providing an extension bit stream. The invention facilitates enhancing a lossy perceptual audio encoding/decoding by an extension that enables mathematically exact reproduction of the original waveform using enhanced de-correlation, and provides additional data for reconstructing at decoder site an intermediate-quality audio signal. The lossless extension can be used to extend the widely used mp3 encoding/decoding to lossless encoding/decoding and superior quality mp3 encoding/de-coding.

Abstract: Soundfield signals such as e.g. Ambisonics carry a representation of a desired sound field. The Ambisonics format is based on spherical harmonic decomposition of the soundfield, and Higher Order Ambisonics uses spherical harmonics of at least 2nd order. However, commonly used loudspeaker setups are irregular and lead to problems in decoder design, A method for improved decoding an audio soundfield representation for audio playback comprises calculating a panning function using a geometrical method based on the positions of a plurality of loudspeakers and a plurality of source directions, calculating a mode matrix from the loudspeaker positions, calculating a pseudo-inverse mode matrix and decoding the audio soundfield representation. The decoding is based on a decode matrix that is obtained from the panning function and the pseudo-inverse mode matrix.

Abstract: Lossless audio coding performs decorrelation and encodes the transformed signal. The encoded bit stream comprises de-correlation parameters and the lossless representation data of the transformed signal. However, in the case of lossy based lossless coding, the additional amount of information exceeds the base layer amount of data. Therefore the additional data cannot be packed completely into the base layer e.g. as ancillary data. The data streams resulting from the combination of lossy coding format with a lossless coding extension are the base layer containing the lossy coding information and the enhancement data stream for rebuilding the mathematically lossless original input signal. Every higher layer depends on the lower layers and can only be reasonably decoded in combination with these lower layers. According to the invention, a special combination of one-time header information with repeated header information in a block structure is used. Assignment information data identify the different layers.

Abstract: In lossy based lossless coding a PCM audio signal passes through a lossy encoder to a lossy decoder. The lossy encoder provides a lossy bit stream. The lossy decoder also provides side information that is used to control the coefficients of a prediction filter that de-correlates the difference signal between the PCM signal and the lossy decoder output. The de-correlated difference signal is lossless encoded, providing an extension bit stream. Instead of, or in addition to, de-correlating in the time domain, a de-correlation in the frequency domain using spectral whitening can be performed. The lossy encoded bit stream together with the lossless encoded extension bit stream form a lossless encoded bitstream. The invention facilitates enhancing a lossy perceptual audio encoding/decoding by an extension that enables mathematically exact reproduction of the original waveform, and provides additional data for reconstructing at decoder site an intermediate-quality audio signal.

Abstract: A compressor device for a compander system has a level detecting/control device and a pre-emphasis device for carrying out an adaptive pre-emphasis filtering. The invention is also directed to an expander device for a compander system with a level detecting/control device and a de-emphasis device for carrying out an adaptive de-emphasis filtering.

Abstract: For the quantisation of spectral data in an audio transform encoder psycho-acoustic information is required, i.e. an approximation of the true masking threshold. According to the invention, for each spectrum to be quantised in the audio signal encoding, an excitation pattern is computed and coded for both long and short window/transform lengths. The excitation patterns are grouped together in a variable-size matrix. A pre-determined sorting order with a fixed number of values only is applied to the excitation pattern data matrix values, and by that re-ordering a quadratic matrix is formed to which matrix' bit planes a SPECK encoding is applied.

Abstract: A compressor device for a compander system has a level detecting/control device and a pre-emphasis device for carrying out an adaptive pre-emphasis filtering. The invention is also directed to an expander device for a compander system with a level detecting/control device and a de-emphasis device for carrying out an adaptive de-emphasis filtering.

Abstract: The invention is related to lossless encoding of a source signal, using a lossy encoded data stream and a lossless extension data stream which together form a lossless encoded data stream for said source signal, whereby lossless audio compression means audio coding with bit-exact reproduction of the original PCM samples at decoder output. The lossy encoding/decoding may be an mp3 coding/decoding. The invention uses an integer MDCT and frequency domain de-correlation and time domain de-correlation for the residual signal of the base-layer lossy audio codec. The exploitation of side information from the lossy base-layer codec allows for reduction of redundancies in the gross bit stream, thus improving the coding efficiency of the lossy based lossless codec.

Abstract: Lossless compression algorithms can only exploit redundancies of the original audio signal to reduce the data rate, but not irrelevancies as identified by psycho-acoustics. Lossless audio coding schemes apply a filter or transform for decorrelation and then encode the transformed signal. The encoded bit stream comprises the parameters of the transform or filter, and the lossless representation of the transformed signal. However, in case of lossy based lossless coding the additional amount of information exceeds the amount of data for the base layer by a multiple of the base layer data amount. Therefore the additional data cannot be packed completely into the base layer data stream e.g. as ancillary data. The at least two data streams resulting from the combination of lossy coding format with a lossless coding extension are the base layer containing the lossy coding information and the enhancement data stream for rebuilding the mathematically lossless original input signal.