应用于短时语音语种识别的时长扩展方法

苗晓晓, 张健, 索宏彬, 周若华, 颜永红

清华大学学报（自然科学版） ›› 2018, Vol. 58 ›› Issue (3) : 254-259.

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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

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
作者信息 +

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
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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。

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.

关键词

语种识别 / 短时 / 时域伸缩 / 语速

Key words

language recognition / short-duration / time-scale modification / speech rate

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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 https://doi.org/10.16511/j.cnki.qhdxxb.2018.25.015
MIAO Xiaoxiao, ZHANG Jian, SUO Hongbin, ZHOU Ruohua, YAN Yonghong. Expanding the length of short utterances for short-duration language recognition[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(3): 254-259 https://doi.org/10.16511/j.cnki.qhdxxb.2018.25.015
中图分类号： TN912.3   

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基金

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）

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