Linear predictive coding

About: Linear predictive coding is a research topic. Over the lifetime, 6565 publications have been published within this topic receiving 142991 citations. The topic is also known as: Linear predictive coding, LPC.

A multi-mode variable rate CELP coder based on frame classification

Abstract: The authors present a modular CELP (code-excited linear prediction) coder which can switch bit-rates in response to local speech characteristics (source-controlled mode) or external network conditions (network-controlled mode). The coder is capable of operating at several bit-rates and is optimized for 16 kb/s, 8 kb/s, and 4 kb/s. A 925-b/s configuration is included for silent frames. The authors present the results of informal MOS tests which show that the variable-rate system running at an average rate of 8 kb/s achieves subjective speech quality close to that of the 16-kb/s fixed-rate system (a difference of less than 0.1 on the MOS scale). >

Efficient representation of short-time phase based on group delay

Abstract: An efficient representation of short-time phase characteristics of speech sounds is proposed, based on findings which suggest the perceptual importance of phase characteristics. Subjective tests indicated that the synthesized speech sounds by the proposed method are indistinguishable from the original speech sounds with a moderate data compression. The proposed representation uses lower-order coefficients of the inverse Fourier transform of the group delay of speech. It also alleviates the voiced/unvoiced decision, which is an indispensable part in conventional speech coding algorithms. These features make our method potentially very useful in many applications like speech morphing.

Data-driven filtering of cepstral time trajectories for robust speech recognition

Abstract: A method and apparatus for speech processing in a distributed speech recognition system having a front-end and a back-end. The speech processing steps in the front-end are as follows: extracting speech features from a speech signal and normalizing the speech features in order to alter the power of the noise component in the modulation spectrum in relation to the power of the signal component, especially with frequencies above 10 Hz. A low-pass filter is then used to filter the normalized modulation spectrum in order to improve the signal-to-noise ratio (SNR) in the speech signal. The combination of feature vector normalization and low-pass filtering is effective in noise removal, especially in a low SNR environment.

Detection and separation of speech event using audio and video information fusion and its application to robust speech interface

Abstract: A method of detecting speech events in a multiple-sound-source condition using audio and video information is proposed. For detecting speech events, sound localization using a microphone array and human tracking by stereo vision is combined by a Bayesian network. From the inference results of the Bayesian network, information on the time and location of speech events can be known. The information on the detected speech events is then utilized in the robust speech interface. A maximum likelihood adaptive beamformer is employed as a preprocessor of the speech recognizer to separate the speech signal from environmental noise. The coefficients of the beamformer are kept updated based on the information of the speech events. The information on the speech events is also used by the speech recognizer for extracting the speech segment.

Single-chip speech recognition system based on 8051 microcontroller core

Abstract: This paper describes a single-chip speech recognition system. It contains the speech functions of prompt, playback, speaker-dependent speech recognition, suitable for the voice activated systems in toys, games, consumer electronics, office devices, etc. The chip is designed based on the SOC (system on chip) philosophy and an 8-bit MCU, RAM, ROM, ADC/DAC, PWM, I/O ports and other peripheral circuits are all embedded in it. Software modules including control/communication, speech coding and speech recognition algorithms are implemented in an 8051 compatible microcontroller core, resulting in the extremely low cost of the chip. The speech recognition adopts the template matching technique. It recognizes up to 20 phrases with an average length of 1 second and the recognition accuracy reaches more than 95% with the background SNR above 10 dB. Speech coding uses continuous variable slope delta modulation (CVSD) algorithm. The bit rate is 16 kbits/s.