利用声音的声学-语音相似性进行多语言音素识别

J. Köhler
{"title":"利用声音的声学-语音相似性进行多语言音素识别","authors":"J. Köhler","doi":"10.21437/ICSLP.1996-556","DOIUrl":null,"url":null,"abstract":"The aim of the work is to exploit the acoustic-phonetic similarities between several languages. In recent work cross-language HMM-based phoneme models have been used only for bootstrapping the language-dependent models and the multi-lingual approach has been investigated only on very small speech corpora. The author introduces a statistical distance measure to determine the similarities of sounds. Further, he presents a new technique to model multi-lingual phonemes. The experiments are conducted with the OGI Multi-Language Telephone Speech Corpus for the languages American English, German and Spanish. In the first experiment phoneme recognition rates between 39.0% and 53.9% are achieved using language-dependent models. Using cross-language models yields improvement for some phonemes, but on average a degradation of recognition performance is observed. However, cross-language models speeds up the cross-language transfer and reduce the size of the phoneme inventory of multi-lingual speech recognition systems. Finally, a new method of modelling multi-lingual phonemes, which can be used for a variety of languages, is presented. This technique reduces the number of phoneme-based units in a multi-lingual speech recognition system.","PeriodicalId":90685,"journal":{"name":"Proceedings : ICSLP. International Conference on Spoken Language Processing","volume":"3 1","pages":"2195-2198"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"101","resultStr":"{\"title\":\"Multi-lingual phoneme recognition exploiting acoustic-phonetic similarities of sounds\",\"authors\":\"J. Köhler\",\"doi\":\"10.21437/ICSLP.1996-556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of the work is to exploit the acoustic-phonetic similarities between several languages. In recent work cross-language HMM-based phoneme models have been used only for bootstrapping the language-dependent models and the multi-lingual approach has been investigated only on very small speech corpora. The author introduces a statistical distance measure to determine the similarities of sounds. Further, he presents a new technique to model multi-lingual phonemes. The experiments are conducted with the OGI Multi-Language Telephone Speech Corpus for the languages American English, German and Spanish. In the first experiment phoneme recognition rates between 39.0% and 53.9% are achieved using language-dependent models. Using cross-language models yields improvement for some phonemes, but on average a degradation of recognition performance is observed. However, cross-language models speeds up the cross-language transfer and reduce the size of the phoneme inventory of multi-lingual speech recognition systems. Finally, a new method of modelling multi-lingual phonemes, which can be used for a variety of languages, is presented. This technique reduces the number of phoneme-based units in a multi-lingual speech recognition system.\",\"PeriodicalId\":90685,\"journal\":{\"name\":\"Proceedings : ICSLP. International Conference on Spoken Language Processing\",\"volume\":\"3 1\",\"pages\":\"2195-2198\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"101\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings : ICSLP. International Conference on Spoken Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21437/ICSLP.1996-556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings : ICSLP. International Conference on Spoken Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21437/ICSLP.1996-556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 101

摘要

这项工作的目的是利用几种语言之间的声学-语音相似性。在最近的工作中,基于跨语言hmm的音素模型仅用于引导语言依赖模型,多语言方法仅在非常小的语料库上进行了研究。作者引入了一种统计距离度量来确定声音的相似度。此外,他还提出了一种新的多语言音素建模技术。使用OGI多语言电话语音语料库对美国英语、德语和西班牙语进行了实验。在第一个实验中,使用语言依赖模型实现了39.0% ~ 53.9%的音素识别率。使用跨语言模型可以提高某些音素的识别性能,但平均而言会降低识别性能。然而,跨语言模型加速了跨语言迁移,减少了多语言语音识别系统的音素库大小。最后,提出了一种新的多语言音素建模方法,该方法可用于多种语言。该技术减少了多语言语音识别系统中基于音素的单元数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-lingual phoneme recognition exploiting acoustic-phonetic similarities of sounds
The aim of the work is to exploit the acoustic-phonetic similarities between several languages. In recent work cross-language HMM-based phoneme models have been used only for bootstrapping the language-dependent models and the multi-lingual approach has been investigated only on very small speech corpora. The author introduces a statistical distance measure to determine the similarities of sounds. Further, he presents a new technique to model multi-lingual phonemes. The experiments are conducted with the OGI Multi-Language Telephone Speech Corpus for the languages American English, German and Spanish. In the first experiment phoneme recognition rates between 39.0% and 53.9% are achieved using language-dependent models. Using cross-language models yields improvement for some phonemes, but on average a degradation of recognition performance is observed. However, cross-language models speeds up the cross-language transfer and reduce the size of the phoneme inventory of multi-lingual speech recognition systems. Finally, a new method of modelling multi-lingual phonemes, which can be used for a variety of languages, is presented. This technique reduces the number of phoneme-based units in a multi-lingual speech recognition system.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信