Speech coding

About: Speech coding is a research topic. Over the lifetime, 14245 publications have been published within this topic receiving 271964 citations.

Adapted local trigonometric transforms and speech processing

Abstract: Uses an algorithm based on the adapted-window Malvar transform to decompose digitized speech signals into a local time-frequency representation. The authors present some applications and experimental results for a signal compression and automatic voiced-unvoiced segmentation. This decomposition provides a method of parameter simplification which appears to be useful for detecting fundamental frequencies, and characterizing formants. >

Decomposition in noise and periodic signal waveforms in waveform interpolation

Abstract: A method of coding a speech signal is described. In accordance with the method, a plurality of sets of indexed parameters are generated based on samples of the speech signal. Each set of indexed parameters corresponds to a waveform characterizing the speech signal at a discrete point in time. Parameters of the plurality of sets are grouped based on index value to form a first set of signals which represents the evolution of characterizing waveform shape; the signals of the first set are filtered to remove low frequency components and thereby produce a second set of signals which represents relatively high rates of evolution of characterizing waveform shape. The speech signal is then coded based on the second set of signals representing high rates of characterizing waveform shape evolution. Coding of the speech signal may further be based on a set of smoothed first signals.

VAD techniques for real-time speech transmission on the Internet

Abstract: We discuss techniques for voice activity detection (VAD) for voice over Internet Protocol (VoIP). VAD aids in reducing the bandwidth requirement of a voice session, thereby using bandwidth efficiently. Such a scheme would be implemented in the application layer. Thus the VAD is independent of the lower layers in the network stack (see Flood, J.E., "Telecommunications Switching - Traffic and Networks", Prentice Hall India). We compare four time-domain VAD algorithms in terms of speech quality, compression level and computational complexity. A comparison of the relative merits and demerits along with the subjective quality of speech after the pruning of silence periods is presented for all the algorithms. A quantitative measurement of speech quality for different algorithms is also presented.

Method and apparatus for processing an input speech signal during presentation of an output audio signal

Abstract: A start of an input speech signal is detected during presentation of an output audio signal and an input start time, relative to the output audio signal, is determined. The input start time is then provided for use in responding to the input speech signal. In another embodiment, the output audio signal has a corresponding identification. When the input speech signal is detected during presentation of the output audio signal, the identification of the output audio signal is provided for use in responding to the input speech signal. Information signals comprising data and/or control signals are provided in response to at least the contextual information provided, i.e., the input start time and/or the identification of the output audio signal. In this manner, the present invention accurately establishes a context of an input speech signal relative to an output audio signal regardless of the delay characteristics of the underlying communication system.

An efficient implementation of the forward and inverse MDCT in MPEG audio coding

Abstract: The modified discrete cosine transform (MDCT) is employed in subband/transform coding schemes as the analysis/synthesis filter bank based on time domain aliasing cancellation (TDAC). The most efficient implementation of the forward and inverse MDCT computation for layer III in MPEG-1 and MPEG-2 international audio coding standards is proposed. It is based on a new fast algorithm for the forward and inverse MDCT computation in the oddly stacked system. The complete signal flow graphs for the implementation of MDCT and inverse MDCT in layer III are also provided.