Research on Speech Recognition by Group Technology

Li Yun; Bao Hong

doi:10.3969/j.issn.1007-7162.2014.02.010

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Research on Speech Recognition by Group Technology

更新时间：2026-05-27

- Research on Speech Recognition by Group Technology
- Vol. 31, Issue 2, Pages: 54-57(2014)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1007-7162.2014.02.010
  CLC： TP391.4
- Online First：06 June 2014，
  
  Published：2014
- 稿件说明：
移动端阅览
李云, 鲍鸿. 语音分组识别技术的研究[J]. 广东工业大学学报, 2014, 31(2): 54-57.

Li Yun, Bao Hong. Research on Speech Recognition by Group Technology[J]. 2014, 31(2): 54-57.
李云, 鲍鸿. 语音分组识别技术的研究[J]. 广东工业大学学报, 2014, 31(2): 54-57. DOI： 10.3969/j.issn.1007-7162.2014.02.010.

Li Yun, Bao Hong. Research on Speech Recognition by Group Technology[J]. 2014, 31(2): 54-57. DOI： 10.3969/j.issn.1007-7162.2014.02.010.

摘要

为了减少语音识别时间，降低系统资源耗费，提出一种针对非特定人、孤立词、大词汇量的语音分组识别算法.运用K均值聚类算法对语音分组，并对语音分组特征进行置信度检验，使分组稳定，保证分组后识别率不下降.通过对非特定人孤立词的语音识别的实验，证实了该方法的有效性.

Abstract

In order to reduce the time of speech recognition and the consumption of system resources

it proposed a method of speech recognition by grouping according to the speaker-independent

isolated words and large vocabularies. The method was based on K-means clustering

and the characteristics of the group were inspected by the confidence in order to make the group stable and ensure that the rate of recognition does not fall after grouping. The experiment results verify the effectiveness of this method.

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