G10L19/06

LINEAR PREDICTION ANALYSIS DEVICE, METHOD, PROGRAM, AND STORAGE MEDIUM

An autocorrelation calculation unit 21 calculates an autocorrelation R.sub.O(i) from an input signal. A prediction coefficient calculation unit 23 performs linear prediction analysis by using a modified autocorrelation R′.sub.O(i) obtained by multiplying a coefficient w.sub.O( ) by the autocorrelation R.sub.O(i). It is assumed here, for each order i of some orders i at least, that the coefficient w.sub.O(i) corresponding to the order i is in a monotonically increasing relationship with an increase in a value that is negatively correlated with a fundamental frequency of the input signal of the current frame or a past frame.

TRUNCATEABLE PREDICTIVE CODING

A method, system, and computer program to encode and decode a channel coherence parameter applied on a frequency band basis, where the coherence parameters of each frequency band form a coherence vector. The coherence vector is encoded and decoded using a predictive scheme followed by a variable bit rate entropy coding.

TRUNCATEABLE PREDICTIVE CODING

A method, system, and computer program to encode and decode a channel coherence parameter applied on a frequency band basis, where the coherence parameters of each frequency band form a coherence vector. The coherence vector is encoded and decoded using a predictive scheme followed by a variable bit rate entropy coding.

Audio Signal Encoding Method and Apparatus
20230039606 · 2023-02-09 ·

An encoding method includes determining an adaptive broadening factor based on a quantized line spectral frequency (LSF) vector of a first channel of a current frame of an audio signal and an LSF vector of a second channel of the current frame, and writing the quantized LSF vector and the adaptive broadening factor into a bitstream.

Audio Signal Encoding Method and Apparatus
20230039606 · 2023-02-09 ·

An encoding method includes determining an adaptive broadening factor based on a quantized line spectral frequency (LSF) vector of a first channel of a current frame of an audio signal and an LSF vector of a second channel of the current frame, and writing the quantized LSF vector and the adaptive broadening factor into a bitstream.

Time-varying always-on compensation for tonally balanced 3D-audio rendering

A system reduces sound coloration caused by rendering of a 3D audio signal. The system renders the 3D audio signal including a plurality of channels using the input audio signal. Input spectra data defining spectral information of the input audio signal is computed. 3D spectra data defining spectral information of a single channel representation of the 3D audio signal is computed. The system generates a tonal balance filter based on the input spectral data and the 3D spectral data. The tonal balance filter, when applied to the 3D audio signal, reduces sound coloration caused by the rendering of the 3D audio signal. The tonal balance filter is applied to the 3D audio signal to generate an output audio signal and the output audio signal is presented via a speaker array.

Time-varying always-on compensation for tonally balanced 3D-audio rendering

A system reduces sound coloration caused by rendering of a 3D audio signal. The system renders the 3D audio signal including a plurality of channels using the input audio signal. Input spectra data defining spectral information of the input audio signal is computed. 3D spectra data defining spectral information of a single channel representation of the 3D audio signal is computed. The system generates a tonal balance filter based on the input spectral data and the 3D spectral data. The tonal balance filter, when applied to the 3D audio signal, reduces sound coloration caused by the rendering of the 3D audio signal. The tonal balance filter is applied to the 3D audio signal to generate an output audio signal and the output audio signal is presented via a speaker array.

LOW-FREQUENCY EMPHASIS FOR LPC-BASED CODING IN FREQUENCY DOMAIN

The invention provides an audio encoder including a combination of a linear predictive coding filter having a plurality of linear predictive coding coefficients and a time-frequency converter, wherein the combination is configured to filter and to convert a frame of the audio signal into a frequency domain in order to output a spectrum based on the frame and on the linear predictive coding coefficients; a low frequency emphasizer configured to calculate a processed spectrum based on the spectrum, wherein spectral lines of the processed spectrum representing a lower frequency than a reference spectral line are emphasized; and a control device configured to control the calculation of the processed spectrum by the low frequency emphasizer depending on the linear predictive coding coefficients of the linear predictive coding filter.

LOW-FREQUENCY EMPHASIS FOR LPC-BASED CODING IN FREQUENCY DOMAIN

The invention provides an audio encoder including a combination of a linear predictive coding filter having a plurality of linear predictive coding coefficients and a time-frequency converter, wherein the combination is configured to filter and to convert a frame of the audio signal into a frequency domain in order to output a spectrum based on the frame and on the linear predictive coding coefficients; a low frequency emphasizer configured to calculate a processed spectrum based on the spectrum, wherein spectral lines of the processed spectrum representing a lower frequency than a reference spectral line are emphasized; and a control device configured to control the calculation of the processed spectrum by the low frequency emphasizer depending on the linear predictive coding coefficients of the linear predictive coding filter.

Characterizing, selecting and adapting audio and acoustic training data for automatic speech recognition systems

A system for and method of characterizing a target application acoustic domain analyzes one or more speech data samples from the target application acoustic domain to determine one or more target acoustic characteristics, including a CODEC type and bit-rate associated with the speech data samples. The determined target acoustic characteristics may also include other aspects of the target speech data samples such as sampling frequency, active bandwidth, noise level, reverberation level, clipping level, and speaking rate. The determined target acoustic characteristics are stored in a memory as a target acoustic data profile. The data profile may be used to select and/or modify one or more out of domain speech samples based on the one or more target acoustic characteristics.