Abstract: A method for audio coding and decoding comprises primary encoding of a present audio signal sample into an encoded representation (T(n)), and non-causal encoding of a first previous audio signal sample into an encoded enhancement representation (ET(n?N+)). The method further comprises providing of the encoded representations to an end user. At the end user, the method comprises primary decoding of the encoded representation (T*(n)) into a present received audio signal sample, and non-causal decoding of the encoded enhancement representation (ET*(n?N+)) into an enhancement first previous received audio signal sample. The method further comprises improving of a first previous received audio signal sample, corresponding to the first previous audio signal sample, based on the enhancement first previous received audio signal sample. Devices and systems for audio coding and decoding are also presented.

Abstract: A voice or audio signal processor for processing received network packets received over a communication network to provide an output signal, the voice or audio signal processor comprising a jitter buffer being configured to buffer the received network packets, a voice or audio decoder being configured to decode the received network packets as buffered by the jitter buffer to obtain a decoded voice or audio signal, a controllable time scaler being configured to amend a length of the decoded voice or audio signal to obtain a time scaled voice or audio signal as the output voice or audio signal, and an adaptation control means being configured to control an operation of the time scaler in dependency on a processing complexity measure.

Abstract: In a method of perceptual transform coding of audio signals in a telecommunication system, performing the steps of determining transform coefficients representative of a time to frequency transformation of a time segmented input audio signal; determining a spectrum of perceptual sub-bands for said input audio signal based on said determined transform coefficients; determining masking thresholds for each said sub-band based on said determined spectrum; computing scale factors for each said sub-band based on said determined masking thresholds, and finally adapting said computed scale factors for each said sub-band to prevent energy loss for perceptually relevant sub-bands.

Abstract: The present invention discloses a pitch detection method and apparatus, which belong to the field of speech and audio. The pitch detection method includes: performing pitch detection on a speech signal in a time domain to obtain an initial pitch period; converting the speech signal to a frequency domain to obtain a frequency spectrum of the speech signal, where the frequency spectrum includes a magnitude spectrum of the frequency spectrum; extracting a feature parameter according to the initial pitch period and the frequency spectrum of the speech signal; and performing fine pitch period detection according to the initial pitch period and the feature parameter to obtain a fine pitch period.

Abstract: The invention relates to a method for processing a multi-channel audio signal which carries a plurality of audio channel signals. The method comprises determining a time-scaling position using the plurality of audio channel signals and time-scaling each audio channel signal of the plurality of audio channel signals according to the time-scaling position to obtain a plurality of time scaled audio channel signals.

Abstract: The signal processing is based on the concept of using a time-domain aliased frame as a basis for time segmentation and spectral analysis, performing segmentation in time based on the time-domain aliased frame and performing spectral analysis based on the resulting time segments. The time resolution of the overall “segmented” time-to-frequency transform can thus be changed by simply adapting the time segmentation to obtain a suitable number of time segments based on which spectral analysis is applied. The overall set of spectral coefficients, obtained for all the segments, provides a selectable time-frequency tiling of the original signal frame.

Abstract: The present disclosure relates to a signal analyzer for processing an overlapped input signal frame comprising 2N subsequent input signal values. The signal analyzer comprises: a windower adapted to window the overlapped input signal frame to obtain a windowed signal, wherein the windower is adapted to zero M+N/2 subsequent input signal values of the overlapped input signal frame, wherein M is equal or greater than 1 and smaller than N/2; and a transformer adapted to transform the remaining 3N/2?M subsequent windowed signal values of the windowed signal using N?M sets of transform parameters to obtain a transformed-domain signal comprising N?M transformed-domain signal values.

Abstract: A method and a device for encoding a high frequency signal, and a method and a device for decoding a high frequency signal are provided, which relate to encoding and decoding technology. The method for encoding a high frequency signal includes: determining a signal class of a high frequency signal of a current frame; smoothing and scaling time envelopes of the high frequency signal of the current frame and obtaining time envelopes of the high frequency signal of the current frame that require to be encoded, if the high frequency signal of the current frame is a non-transient signal and a high frequency signal of the previous frame is a transient signal; and quantizing and encoding the time envelopes of the high frequency signal of the current frame that require to be encoded, and frequency information and signal class information of the high frequency signal of the current frame.

Abstract: Embodiments of the present invention provide a signal classification method and device, and encoding and decoding methods and devices. The encoding method includes dividing a current frame into a low-frequency band signal and a high-frequency band signal, attenuating the high-frequency band signal or a to-be-encoded characteristic parameter of the high-frequency band signal according to an energy attenuation value of the low-frequency band signal, where the energy attenuation value indicates energy attenuation of the low-frequency band signal caused by encoding of the low-frequency band signal, and encoding the attenuated high-frequency band signal or the attenuated to-be-encoded characteristic parameter of the high-frequency band signal. The technical solutions according to the embodiments of the present invention can improve the effect of combining the low-frequency band signal and the high-frequency band signal at the decoder.

Abstract: A method and apparatus for providing signal processing coefficients for processing an input signal at a predetermined signal processing sampling rate, wherein the input signal is received at an input signal sampling rate, the method comprising the steps of computing a correlation or covariance function based on the received input signal at the input signal sampling rate to provide correlation or covariance coefficients at the input signal sampling rate, re-sampling the computed correlation or covariance coefficients having the input signal sampling rate to provide correlation or covariance coefficients at the predetermined signal processing sampling rate, and calculating the signal processing coefficients based on the correlation or covariance coefficients at the predetermined signal processing sampling rate.

Abstract: Embodiments of the present invention provide a signal classification method and device, and encoding and decoding methods and devices. The encoding method includes: dividing a current frame into a low-frequency band signal and a high-frequency band signal; attenuating the high-frequency band signal or a to-be-encoded characteristic parameter of the high-frequency band signal according to an energy attenuation value of the low-frequency band signal, where the energy attenuation value indicates energy attenuation of the low-frequency band signal caused by encoding of the low-frequency band signal; and encoding the attenuated high-frequency band signal or the attenuated to-be-encoded characteristic parameter of the high-frequency band signal. The technical solutions according to the embodiments of the present invention can improve the effect of combining the low-frequency band signal and the high-frequency band signal at the decoder.

Abstract: A voice quality enhancement (VQE) detector for a network element receiving an audio signal from a previous network element of a network, wherein said voice quality enhancement detector is adapted: to perform a voice quality enhancement detection based on the received audio signal, wherein said voice quality enhancement detection comprises detecting that at least one voice quality enhancement function, VQEF, was applied to the received audio signal by at least one previous network element of the network; and to control a voice quality enhancement processing of the received audio signal depending on the detection result.

Abstract: The present disclosure relates to a signal analyzer for processing an overlapped input signal frame comprising 2N subsequent input signal values. The signal analyzer comprises: a windower adapted to window the overlapped input signal frame to obtain a windowed signal, wherein the windower is adapted to zero M+N/2 subsequent input signal values of the overlapped input signal frame, wherein M is equal or greater than 1 and smaller than N/2; and a transformer adapted to transform the remaining 3N/2?M subsequent windowed signal values of the windowed signal using N?M sets of transform parameters to obtain a transformed-domain signal comprising N?M transformed-domain signal values.

Abstract: The signal processing is based on the concept of using a time-domain aliased frame as a basis for time segmentation and spectral analysis, performing segmentation in time based on the time-domain aliased frame and performing spectral analysis based on the resulting time segments. The time resolution of the overall “segmented” time-to-frequency transform can thus be changed by simply adapting the time segmentation to obtain a suitable number of time segments based on which spectral analysis is applied. The overall set of spectral coefficients, obtained for all the segments, provides a selectable time-frequency tiling of the original signal frame.

Abstract: The signal processing is based on the concept of using a time-domain aliased (12, TDA) frame as a basis for time segmentation (14) and spectral analysis (16), performing segmentation in time based on the time-domain aliased frame and performing spectral analysis based on the resulting time segments. The time resolution of the overall ?segmented? time-to-frequency transform can thus be changed by simply adapting the time segmentation to obtain a suitable number of time segments based on which spectral analysis is applied. The overall set of spectral coefficients, obtained for all the segments, provides a selectable time-frequency tiling of the original signal frame.

Abstract: A method for perceptual spectral decoding comprises decoding of spectral coefficients recovered from a binary flux into decoded spectral coefficients of an initial set of spectral coefficients. The initial set of spectral coefficients are spectrum filled. The spectrum filling comprises noise filling of spectral holes by setting spectral coefficients in the initial set of spectral coefficients not being decoded from the binary flux equal to elements derived from the decoded spectral coefficients. The set of reconstructed spectral coefficients of a frequency domain formed by the spectrum filling is converted into an audio signal of a time domain. A perceptual spectral decoder comprises a noise filler, operating according to the method for perceptual spectral decoding.

Abstract: A vector quantizer includes a lattice quantizer (10) approximating a vector x by a lattice vector belonging to a lattice ?0. A lattice vector decomposer (14) connected to the lattice quantizer successively decomposes the lattice vector into a sequence of quotient vectors y, and a sequence of remainder vectors ri on successive lattices ?I?1 by lattice division with a corresponding predetermined sequence of integers pi?2, where i=1 . . . k and k is a positive integer representing the number of elements in each sequence.

Abstract: A network processing node (e.g., MGW, MRFP) and method are described herein that can: (1) receive packets on a first heterogeneous link (e.g., wireless link); (2) manipulate the received packets based on known characteristics about a second heterogeneous link (e.g., “Internet” link); and (3) send the manipulated packets on the second heterogeneous link (e.g., “Internet” link). For example, the network processing node can manipulate the received packets by adding redundancy, removing redundancy, frame aggregating (re-packetizing), recovering lost packets and/or re-transmitting packets.

Abstract: A voice activity detection apparatus (1) comprising: a signal condition analyzing unit (3) which analyses at least one signal parameter of an input signal to detect a signal condition SC of said input signal; at least two voice activity detection units (4-i) comprising different voice detection characteristics, wherein each voice activity detection unit (4-i) performs separately a voice activity detection of said input signal to provide a voice activity detection decision VADD; and a decision combination unit (5) which combines the voice activity detection decisions VADDs provided by said voice activity detection units (4-i) depending on the detected signal condition SC to provide a combined voice activity detection decision cVADD.

Abstract: In signal processing using digital filtering the representation of a filter is adapted depending on the filter characteristics If e.g. a digital filter is represented by filter coefficients for transform bands Nos. 0, 1, . . . , K in the frequency domain, a reduced digital filter having coefficients for combined transform bands, i.e. subsets of the transformed bands, Nos. 0, 1, . . . , L, is formed and only these coefficients are stored. When the actual filtering in the digital filter is to be performed, an actual digital filter is obtained by expanding the coefficients of the reduced digital filter according to a mapping table and then used instead of the original digital filter.