Speech coding

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

Method and device for converting speech

Abstract: Electronic device and method for obtaining a digital speech signal and a control command relating to thedigital speech signal while obtaining the digital speech signal, and for temporally associating the control command with a substantially corresponding time instant in the digital speech signal towhich the control command was directed, wherein the control command determines one or more punctuation marks or another, optionally symbolic, elements to be at least logically positioned at a text location corresponding to the communication instant relative to the digital speech signal so as to cultivate the speech to text conversion procedure.

Real-time vector APC speech coding at 4800 bps with adaptive postfiltering

Abstract: An improved Vector APC (VAPC) speech coder at 4800 bps produces speech with very good communications quality while maintaining a complexity low enough to allow a real-time implementation with at most two commercially available DSP chips. The VAPC algorithm combines APC with vector quantization and incorporates analysis-by-synthesis, perceptual noise weighting, and adaptive postfiltering. A novel adaptive postfiltering technique helps to achieve an essentially inaudible level of coding noise. Real-time software has been developed for an implementation using the AT&T DSP32 floating-point processor chip. The overall complexity of the implemented VAPC system is about 3 million multiply-adds/second of computation and 6 kwords of memory.

Quantization procedures for the excitation in CELP coders

Abstract: Past research on CELP (Code-Excited Linear Predictive) coders has mainly concentrated on the feasibility of the CELP concept and on the reduction of the computational complexity. In this paper we address the problem of finding and encoding the excitation parameters with a limited bit rate, such that high quality speech coding in the 4.8 - 7.2 kb/s range becomes feasible. First, we examine the effect of the various excitation parameters such as code book size, code book population, order of the long-term predictor and update rate on the quality of the reconstructed speech. Second, we investigate procedures for designing and incorporating quantizers for the parameters involved. Finally, using both scalar and vector quantization techniques for the LPC coefficients, we simulated 4.8 kb/s and 7.2 kb/s coders. We also report on the use of postfiltering to further improve the performance of the CELP coder.

On the automatic segmentation of speech signals

Abstract: For large vocabulary and continuous speech recognition, the sub-word-unit-based approach is a viable alternative to the whole-word-unit-based approach. For preparing a large inventory of subword units, an automatic segmentation is preferrable to manual segmentation as it substantially reduces the work associated with the generation of templates and gives more consistent results. In this paper we discuss some methods for automatically segmenting speech into phonetic units. Three different approaches are described, one based on template matching, one based on detecting the spectral changes that occur at the boundaries between phonetic units and one based on a constrained-clustering vector quantization approach. An evaluation of the performance of the automatic segmentation methods is given.

ECG signal compression using analysis by synthesis coding

Abstract: An electrocardiogram (ECG) compression algorithm, called analysis by synthesis ECG compressor (ASEC), is introduced. The ASEC algorithm is based on analysis by synthesis coding, and consists of a beat codebook, long and short-term predictors, and an adaptive residual quantizer. The compression algorithm uses a defined distortion measure in order to efficiently encode every heartbeat, with minimum bit rate, while maintaining a predetermined distortion level. The compression algorithm was implemented and tested with both the percentage rms difference (PRD) measure and the recently introduced weighted diagnostic distortion (WDD) measure. The compression algorithm has been evaluated with the MIT-BIH Arrhythmia Database. A mean compression rate of approximately 100 bits/s (compression ratio of about 30:1) has been achieved with a good reconstructed signal quality (WDD below 4% and PRD below 8%). The ASEC was compared with several well-known ECG compression algorithms and was found to be superior at all tested bit rates. A mean opinion score (MOS) test was also applied. The testers were three independent expert cardiologists. As In the quantitative test, the proposed compression algorithm was found to be superior to the other tested compression algorithms.