Topic
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.
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TL;DR: In this paper, an unvoiced speech performance was improved in low-rate multi-pulse coders by employing a simple architecture with an output quality comparable to code excited linear predictive (CELP) coding.
Abstract: Improved unvoiced speech performance in low-rate multi-pulse coders is achieved by employing a multi-pulse architecture that is simple in implementation but with an output quality comparable to code excited linear predictive (CELP) coding. A hybrid architecture is provided in which a stochastic excitation model that is used during unvoiced speech is also capable of modeling voiced speech by use of random codebook excitation. A modified method for calculating the gain during stochastic excitation is also provided.
73 citations
TL;DR: A novel approach to the voiced-unvoiced-silence detection problem is proposed in which a spectral characterization of each of the three classes of signal is obtained during a training session, and an LPC distance measure and an energy distance are nonlinearly combined to make the final discrimination.
Abstract: One of the most difficult problems in speech analysis is reliable discrimination among silence, unvoiced speech, and voiced speech which has been transmitted over a telephone line. Although several methods have been proposed for making this three-level decision, these schemes have met with only modest success. In this paper, a novel approach to the voiced-unvoiced-silence detection problem is proposed in which a spectral characterization of each of the three classes of signal is obtained during a training session, and an LPC distance measure and an energy distance are nonlinearly combined to make the final discrimination. This algorithm has been tested over conventional switched telephone lines, across a variety of speakers, and has been found to have an error rate of about 5 percent, with the majority of the errors (about \frac{2}{3} ) occurring at the boundaries between signal classes. The algorithm is currently being used in a speaker-independent word recognition system.
73 citations
26 Apr 1985
TL;DR: Preliminary results indicate that speech and noisy speech synthesized based on this model do not have the "buzziness" typically associated with vocoder speech and is essentially the same as the original speech or the noisy speech in both intelligibility and quality.
Abstract: A new model-based speech analysis/synthesis system is presented in this paper. In this model, the short-time spectrum of speech is modeled as the product of an excitation spectrum and a spectral envelope. The spectral envelope is some smoothed version of the speech spectrum and the excitation spectrum is represented by the pitch period and a voiced/unvoiced (V/UV) decision for each harmonic. In speech analysis, the model parameters are estimated by explicit comparison between the original speech spectrum and the synthetic speech spectrum. Preliminary results indicate that speech and noisy speech synthesized based on this model do not have the "buzziness" typically associated with vocoder speech and is essentially the same as the original speech or the noisy speech in both intelligibility and quality. Potential applications of this new model and its parameter estimation include high quality speech analysis/synthesis, time scale modification of speech and noisy speech, and pitch detection.
73 citations
07 May 1996
TL;DR: This work provides evidence for the claim that a modern continuous speech recognizer can be used successfully in "black-box" fashion for robustly interpreting spontaneous utterances in a dialogue with a human.
Abstract: This paper presents a new technique for overcoming several types of speech recognition errors by post-processing the output of a continuous speech recognizer. The post-processor output contains fewer errors, thereby making interpretation by higher-level modules, such as a parser, in a speech understanding system more reliable. The primary advantage to the post-processing approach over existing approaches for overcoming SR errors lies in its ability to introduce options that are not available in the SR module's output. This work provides evidence for the claim that a modern continuous speech recognizer can be used successfully in "black-box" fashion for robustly interpreting spontaneous utterances in a dialogue with a human.
72 citations
Patent•
IBM1
TL;DR: In this paper, an Acoustic Processor is used to produce a Mel-Cepstrum Vector and Pitch, which is then recalibrated and encoded over a narrow-band channel.
Abstract: The device and method of the invention receives a digital speech signal, which is processed by an Acoustic Processor to produce a Mel-Cepstrum Vector and Pitch. This is recalibrated and encoded. The encoded signal is transmitted over a narrow-band Channel, then decoded, split and recalibrated. From the split signals, one signal feeds a Statistical Processor which produces Recognized Text. Another signal feeds a Regenerator, which produces Regenerated Speech. The device and method according to the invention achieve simultaneously very perceptive Automatic Speech Recognition and high quality VoCoding, using Speech communicated or stored via a Channel with narrow-bandwidth; very perceptive Automatic Speech Recognition on a Client & Server system without a need to store or to communicate wide-bandwidth Speech signals; very perceptive Automatic Speech Recognition with Deferred Review and Editing without storage of wide-bandwidth Speech signals; better feedback in a system for Automatic Speech Recognition particularly for Deferred Automatic Speech Recognition; and good usability for unified Automatic Speech Recognition and VoCoding.
72 citations