Abstract: The present disclosure relates to a method and system for performing packet loss concealment using a neural network system. The method comprises obtaining a representation of an incomplete audio signal, inputting the representation of the incomplete audio signal to an encoder neural network and outputting a latent representation of a predicted complete audio signal. The latent representation is input to a decoder neural network which outputs a representation of a predicted complete audio signal comprising a reconstruction of the original portion of the complete audio signal, wherein said encoder neural network and said decoder neural network have been trained with an adversarial neural network.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: Embodiments relate to an audio processing unit that includes a buffer, bitstream payload deformatter, and a decoding subsystem. The buffer stores at least one block of an encoded audio bitstream. The block includes a fill element that begins with an identifier followed by fill data. The fill data includes at least one flag identifying whether enhanced spectral band replication (eSBR) processing is to be performed on audio content of the block. A corresponding method for decoding an encoded audio bitstream is also provided.

Abstract: The invention provides an efficient implementation of cross-product enhanced high-frequency reconstruction (HFR), wherein a new component at frequency Q?+r?0 is generated on the basis of existing components at ? and ?+?0. The invention provides a block-based harmonic transposition, wherein a time block of complex subband samples is processed with a common phase modification. Superposition of several modified samples has the net effect of limiting undesirable intermodulation products, thereby enabling a coarser frequency resolution and/or lower degree of oversampling to be used. In one embodiment, the invention further includes a window function suitable for use with block-based cross-product enhanced HFR. A hardware embodiment of the invention may include an analysis filter bank, a subband processing unit configurable by control data and a synthesis filter bank.

Abstract: The present document relates to audio coding systems. In particular, the present document relates to efficient methods and systems for parametric multi-channel audio coding. An audio encoding system configured to generate a bitstream indicative of a downmix signal and spatial metadata for generating a multi-channel upmix signal from the downmix signal is described. The system comprises a downmix processing unit configured to generate the downmix signal from a multi-channel input signal; wherein the downmix signal comprises m channels and wherein the multi-channel input signal comprises n channels; n, m being integers with m<n. Furthermore, the system comprises a parameter processing unit configured to determine the spatial metadata from the multi-channel input signal.

Abstract: A method (910) for rendering an audio signal in a virtual reality rendering environment (180) is described. The method (910) comprises rendering (911) an origin audio signal of an audio source (311, 312, 313) from an origin source position on an origin sphere (114) around an origin listening position (301) of a listener (181). Furthermore, the method (900) comprises determining (912) that the listener (181) moves from the origin listening position (301) to a destination listening position (302). In addition, the method (900) comprises determining (913) a destination source position of the audio source (311, 312, 313) on a destination sphere (114) around the destination listening position (302) based on the origin source position, and determining (914) a destination audio signal of the audio source (311, 312, 313) based on the origin audio signal.

Abstract: A method for representing a second presentation of audio channels or objects as a data stream, the method comprising the steps of: (a) providing a set of base signals, the base signals representing a first presentation of the audio channels or objects; (b) providing a set of transformation parameters, the transformation parameters intended to transform the first presentation into the second presentation; the transformation parameters further being specified for at least two frequency bands and including a set of multi-tap convolution matrix parameters for at least one of the frequency bands.

Abstract: The present invention relates to a method and device for processing a first and a second audio signal representing an input binaural audio signal acquired by a binaural recording device. The present invention further relates to a method for rendering a binaural audio signal on a speaker system. The method for processing a binaural signal comprising extracting audio information from the first audio signal, computing a band gain for reducing noise in the first audio signal and applying the band gains to respective frequency bands of the first audio signal in accordance with a dynamic scaling factor, to provide a first output audio signal. Wherein the dynamic scaling factor has a value between zero and one and is selected so as to reduce quality degradation for the first audio signal.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: The invention provides methods and devices for stereo encoding and decoding using complex prediction in the frequency domain. In one embodiment, a decoding method, for obtaining an output stereo signal from an input stereo signal encoded by complex prediction coding and comprising first frequency-domain representations of two input channels, comprises the upmixing steps of: (i) computing a second frequency-domain representation of a first input channel; and (ii) computing an output channel on the basis of the first and second frequency-domain representations of the first input channel, the first frequency-domain representation of the second input channel and a complex prediction coefficient. The upmixing can be suspended responsive to control data.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag. The high frequency regeneration is performed as a post-processing operation with a delay of 3010 samples per audio channel.

Abstract: A method for coding includes; segmenting an image into blocks; grouping blocks into a number of subsets; coding, using an entropy coding module, each subset, by associating digital information with symbols of each block of a subset, including, for the first block of the image, initializing state variables of the coding module; and generating a data sub-stream representative of at least one of the coded subsets of blocks. Where a current block is the first block to be coded of a subset, symbol occurrence probabilities for the first current block are determined based on those for a coded and decoded predetermined block of at least one other subset. Where the current block is the last coded block of the subset: writing, in the sub-stream representative of the subset, the entire the digital information associated with the symbols during coding of the blocks of the subset, and implementing the initializing sub-step.

Abstract: A deep-learning-based system for performing automated multitrack mixing based on a plurality of input audio tracks is described herein. The system comprises one or more instances of a deep-learning-based first network and one or more instances of a deep-learning-based second network. Particularly, the first network is configured to, based on the 5 input audio tracks, generate parameters for use in the automated multitrack mixing. The second network is configured to, based on the parameters, apply signal processing and at least one mixing gain to the input audio tracks, for generating an output mix of the audio tracks.

Abstract: A method of coding at least one image comprising the steps of splitting the image into a plurality of blocks, of grouping said blocks into a predetermined number of subsets of blocks, of coding each of said subsets of blocks in parallel, the blocks of a subset considered being coded according to a predetermined sequential order of traversal. The coding step comprises, for a current block of a subset considered, the sub-step of predictive coding of said current block with respect to at least one previously coded and decoded block, and the sub-step of entropy coding of said current block on the basis of at least one probability of appearance of a symbol.

Abstract: Diffuse or spatially large audio objects may be identified for special processing. A decorrelation process may be performed on audio signals corresponding to the large audio objects to produce decorrelated large audio object audio signals. These decorrelated large audio object audio signals may be associated with object locations, which may be stationary or time-varying locations. For example, the decorrelated large audio object audio signals may be rendered to virtual or actual speaker locations. The output of such a rendering process may be input to a scene simplification process. The decorrelation, associating and/or scene simplification processes may be performed prior to a process of encoding the audio data.