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清华大学学报(自然科学版)  2018, Vol. 58 Issue (3): 254-259    DOI: 10.16511/j.cnki.qhdxxb.2018.25.015
  计算机科学与技术 本期目录 | 过刊浏览 | 高级检索 |
应用于短时语音语种识别的时长扩展方法
苗晓晓1,2, 张健1,2, 索宏彬1,2, 周若华1,2, 颜永红1,2,3
1. 中国科学院 声学研究所, 语言声学与内容理解重点实验室, 北京 100190;
2. 中国科学院大学, 北京 100190;
3. 中国科学院 新疆理化技术研究所, 新疆民族语音语言信息处理实验室, 新疆 830011
Expanding the length of short utterances for short-duration language recognition
MIAO Xiaoxiao1,2, ZHANG Jian1,2, SUO Hongbin1,2, ZHOU Ruohua1,2, YAN Yonghong1,2,3
1. Key Laboratory of Speech Acoustics and Content Understanding, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China;
2. University of Chinese Academy of Sciences, Beijing 100190, China;
3. Xinjiang Laboratory of Minority Speech and Language Information Processing, Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Xinjiang 830011, China
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摘要 为解决待识别语音时长小于10 s时,语种识别性能急剧下降的问题,该文提出应用语音时域伸缩(time-scale modification,TSM)技术改变语音的长度(从而改变了语速),并保持其他频域信息不变。首先,对一段待识别语音,应用TSM技术转换为多条时域压缩和时域拉伸后的语音;其次,将这些不同语速的语音与原语音拼接起来,生成一个时长较长的语音;最后,送入语种识别系统进行识别。实验结果表明:所提出的语音时长扩展算法可以显著提升短时语音的语种识别性能。
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苗晓晓
张健
索宏彬
周若华
颜永红
关键词 语种识别短时时域伸缩语速    
Abstract:The language recognition (LR) accuracy is often significantly reduced when the test utterance duration is as short as 10 s or less. This paper describes a method to extend the utterance length using time-scale modification (TSM) which changes the speech rate without changing the spectral information. The algorithm first converts an utterance to several time-stretched or time-compressed versions using TSM. These modified versions with different speech rates are concatenated together with the original one to form a long-duration signal, which is subsequently fed into the LR system. Tests demonstrate that this duration modification method dramatically improves the performance for short utterances.
Key wordslanguage recognition    short-duration    time-scale modification    speech rate
收稿日期: 2017-09-26      出版日期: 2018-03-14
ZTFLH:  TN912.3  
基金资助:国家重点研发计划重点专项(2016YFB0801203,2016YFB0801200);国家自然科学基金资助项目(11590770-4,U1536117,11504406,11461141004)
通讯作者: 周若华,研究员,E-mail:zhouruohua@hccl.ioa.ac.cn     E-mail: zhouruohua@hccl.ioa.ac.cn
作者简介: 苗晓晓(1994-),女,博士研究生。
引用本文:   
苗晓晓, 张健, 索宏彬, 周若华, 颜永红. 应用于短时语音语种识别的时长扩展方法[J]. 清华大学学报(自然科学版), 2018, 58(3): 254-259.
MIAO Xiaoxiao, ZHANG Jian, SUO Hongbin, ZHOU Ruohua, YAN Yonghong. Expanding the length of short utterances for short-duration language recognition. Journal of Tsinghua University(Science and Technology), 2018, 58(3): 254-259.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2018.25.015  或          http://jst.tsinghuajournals.com/CN/Y2018/V58/I3/254
  图1 RTISI算法图示
  图2 RTISI算法处理示例语音波形图
  图3 RTISI算法处理示例语音频谱图
  表1 原语音和经过TSM 变换后语音的识别性能对比(%)
  表2 原语音和经过TSM 变换后语音拼接的识别性能(%)
  表3 拼接一条慢速语音和一条快速语音的性能(%)
  表4 拼接4条不同语速语音的性能(%)
  表5 拼接6条和8条不同语速语音的性能(%)
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