Qualcomm Incorporated

Petr Motlicek

Harinath Garudadri

Hynek Hermansky

Naveen Srinivasamurthy

Nelson H Morgan

Naveen B Srinivasamurthy

Charles C Wooters

Sriram Ganapathy

Andre Gustavo Adami

Maria Carmen Benitez Ortuzar

Lukas Burget

Stephane N Dupont

Sunil Sivadas

Frantisek Grezl

Pratibha Jain

Sachin Kajarekar

A technique of spectral noise shaping in an audio coding system is disclosed. Frequency decomposition of an input audio signal is performed to obtain multiple frequency sub-bands that closely follow critical bands of human auditory system decomposition. The tonality of each sub-band is determined. If a sub-band is tonal, time domain linear prediction (TDLP) processing is applied to the sub-band, yielding a residual signal and linear predictive coding (LPC) coefficients of an all-pole model representing the sub-band signal. The residual signal is further processed using a frequency domain linear prediction (FDLP) method. The FDLP parameters and LPC coefficients are transferred to a decoder. At the decoder, an inverse-FDLP process is applied to the encoded residual signal followed by an inverse TDLP process, which shapes the quantization noise according to the power spectral density of the original sub-band signal. Non-tonal sub-band signals bypass the TDLP process.

Spectral noise shaping in audio coding based on spectral dynamics in frequency sub-bands

In an apparatus and method, time-varying signals are processed and encoded via a frequency domain linear prediction (FDLP) scheme to arrive at an all-pole model. Residual signals resulted from the scheme are estimated and transformed into a time domain signal. Through the process of heterodyning, the time domain signal is frequency shifted toward the baseband level as a downshifted carrier signal. Quantized values of the all-pole model and the frequency transform of the downshifted carrier signal are packetized as encoded signals suitable for transmission or storage. To reconstruct the time-varying signals, the encoded signals are decoded. The decoding process is basically the reverse of the encoding process.

Processing of excitation in audio coding and decoding

In an apparatus and method, time-varying signals are processed and encoded via a frequency domain linear prediction (FDLP) scheme to arrive at an all-pole model. Residual signals resulted from the scheme are estimated. Quantized values of the all-pole model and the residual signals are packetized as encoded signals suitable for transmission or storage. To reconstruct the time-varying signals, the encoded signals are decoded. The decoding process is basically the reverse of the encoding process.

Signal coding and decoding based on spectral dynamics

A distributed voice recognition system and method for obtaining acoustic features and speech activity at multiple frequencies by extracting high frequency components thereof on a device, such as a subscriber station and transmitting them to a network server having multiple stream processing capability, including cepstral feature processing, MLP nonlinear transformation processing, and multiband temporal pattern architecture processing. The features received at the network server are processed using all three streams, wherein each of the three streams provide benefits not available in the other two, thereby enhancing feature interpretation. Feature extraction and feature interpretation may operate at multiple frequencies, including but not limited to 8 kHz, 11 kHz, and 16 kHz.

Multistream network feature processing for a distributed speech recognition system

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Martigny-Croix, Switzerland

Petr Motlicek