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Network speech recognition method in English oral language machine examination system

A recognition method and network voice technology, applied in voice recognition, voice analysis, instruments, etc., can solve problems that affect real-time performance and regular effects

Inactive Publication Date: 2012-05-02
SOUTHEAST UNIV
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Problems solved by technology

There are two problems with this long-term cepstrum mean normalization (CMN) noise reduction technique. One is that the frequency of phonemes in the input sentence will change. The size directly affects the regular effect
The second is that the calculation can only be calculated after the calculation is completed until the end point. Affected real-time
However, traditional VQ and DP methods can only be applied to a specific person's speech recognition system

Method used

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  • Network speech recognition method in English oral language machine examination system
  • Network speech recognition method in English oral language machine examination system
  • Network speech recognition method in English oral language machine examination system

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Embodiment Construction

[0089] The technical solution of the present invention will be further elaborated below in conjunction with the accompanying drawings.

[0090] figure 1 It is an asymmetric DP path.

[0091] figure 2 It is a flowchart of the implementation steps.

[0092] 1. Input the voice signal a'(t) in the oral English test system, where t is a time variable;

[0093] 2. Preprocessing and feature extraction

[0094] preprocessing stage

[0095] 1) Sampling the voice signal: Sampling the voice signal in the English oral computer test system with a frequency f s is 8kHz sampling, the sampled signal is s(t), s ( t ) = a ′ ( t ) · δ T ( t ) = a ′ ( t ) ...

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Abstract

The invention relates to a scheme of realizing network speech recognition in an English oral language machine examination system. According to the scheme, traditional spectral subtraction (SS) noise reduction technology and cepstral mean normalization (CMN) noise reduction technology are improved, combined with a probability scale DP identification method of a continuous state hidden Markov model(HMM), the invention provides a network speech recognition scheme of unspecified people in an English network examination system, and by utilizing the scheme, a network speech recognition apparatus in a physical environment is realized. By employing the above method, an SS method with input amplitude spectrum self-adapting and a CMN method based on progressive adaptive mode MAP algorithm are combined, and influence of ambient noise on an identification system is substantially reduced. Simultaneously, according to the scheme, based on a traditional DP method, by utilizing a DP algorithm of probability scale, recognition is carried out, thus a DSP speech recognition apparatus can be applied to speech recognition of unspecified people of different outdoor occasions, and a recognition system scope and recognition precision are raised.

Description

technical field [0001] The invention relates to a network voice recognition technology, in particular to a non-specific network voice recognition scheme in an English oral computer test system. Background technique [0002] The Department of Higher Education of the Ministry of Education of my country launched the computer-based and network-based CET-4 and CET-6 test projects in May 2007, and implemented CET-4 network test points in 53 colleges and universities across the country on December 20, 2008. With the development of my country's CET-4 and CET-6 test sites, it will completely change the disadvantages of relying mainly on paper-based test systems in language tests for a long time. It is a huge challenge for both candidates and college English teachers. a revolution. However, the computer-based oral English test system generally provides English recognition and evaluation services between the terminal and the server through the network, and the general requirements for ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/00G10L15/02G10L15/08G10L21/02G10L15/30
Inventor 刘健刚李霄翔储琢佳张潇丹董静赵力张萍李鲁
Owner SOUTHEAST UNIV
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