End-point detecting method applied to speech identification system

An endpoint detection and speech recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve problems such as performance degradation, high computing efficiency, and inability to establish corresponding models, and achieve the effect of easy onlineization

Inactive Publication Date: 2008-11-19
IFLYTEK CO LTD
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Problems solved by technology

The method based on characteristics such as energy and zero-crossing rate has simple logic, high computational efficiency, and is easy to apply to real-time systems. This type of method works well in the case of high SNR, but the performance drops sharply in the case of low SNR. decline
The method based on the model classifier can achieve better re

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  • End-point detecting method applied to speech identification system
  • End-point detecting method applied to speech identification system
  • End-point detecting method applied to speech identification system

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Embodiment Construction

[0030] The present invention adopts the way of combining the energy double-threshold algorithm and the judgment of the model classifier, that is, a detection-verification strategy to detect the endpoint of the voice signal. In the detection stage, the energy double-threshold algorithm is used for the initial energy judgment; in the verification stage, the segment zero-crossing rate is first used to judge, and then the model classifier is used for further verification. The steps of the present invention include:

[0031] model training;

[0032] Perform energy preliminary judgment, determine the threshold value according to the energy feature, and find the possible starting point of speech;

[0033] Model classifier judgment, further verification of the speech start point obtained in the energy preliminary judgment stage and the zero-crossing rate judgment stage;

[0034] Determine the end point of the speech and confirm the speech segment.

[0035] Model training: First, co...

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Abstract

The invention relates to a terminal detection method for a voice recognition system. The method combines energy double-threshold algorithm with judgment by a model classifier, namely, a detection-verification strategy, to detect terminals of voice signals. In the detection process, energy is initially judged through energy double-threshold algorithm; in the verification process, firstly, a segmental zero-passage rate is judged and then the model classifier is adopted for further verification; the detection-verification strategy includes the following steps: model training, initial energy judging, zero-passage rate judging, model classifier judging, voice terminal determination and voice segment confirmation. The method can effectively and accurately locate the terminals of the voice; meanwhile, the method is easy to realize on line and is applicable to voice real time recognition systems.

Description

technical field [0001] The invention relates to the field of speech recognition. Background technique [0002] In the speech recognition system, the digital speech signal is composed of a mixture of silent segments, noise segments and speech segments. In this signal, speech is distinguished from various non-speech signals, and the accurate determination of the speech signal is called an endpoint. Detection or Voice Activity Detection (Voice Activity Detection, VAD). Whether the endpoint detection is correct or not will directly affect the performance of the speech recognition system, which is manifested in two aspects: accuracy and speed: first, if the silence and noise segments in the signal are removed, it will help the system to accurately extract speech features and improve speech recognition. Second, if the signal to be processed contains a large number of non-speech parts, an effective endpoint detection algorithm can remove the calculation of the noise segment, the c...

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Application Information

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IPC IPC(8): G10L15/04G10L15/06G10L11/02G10L15/08G10L25/87
Inventor 高建清胡国平胡郁刘庆峰王仁华
Owner IFLYTEK CO LTD
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