User Friendly Speech Recognition Algorithm with Adaptability for Environments and Users

用户友好的语音识别算法，具有对环境和用户的适应性

基本信息

批准号：
15300060
负责人：
SHIKANO Kiyohiro
金额：
$ 10.3万
依托单位：
Nara Institute of Science and Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2006
项目状态：
已结题

项目摘要

The research plan includes the following topics,1. Noise reduction signal processing, accurate phoneme modeling, and speaker and environment adaptation.2. Task adapted language model for accepting spontaneous utterances.3. Hands-free speech recognition interface.4. Study of human factors for speech dialog system.These investigations have been studied based on real world speech dialog systems.The main attained research results are summarized as follows.1. Unsupervised speaker adaptation algorithm based on an arbitrary utterance has been developed, which takes only several seconds, and shows almost same accuracy as supervised adaptation MLLR based on 50 utterances.2. Task adapted language models have been developed for children and adults using two year Takemaru-kun transcribed texts. By introducing parallel decoding for children and adults, we attain the improvements of word accuracy and response accuracy.3. Hands-free speech recognition has been implemented based on null-beamformer type SSA (Spatial Subtraction Array) and BSSA (Blind SSA) with SIMO-ICA.4. We have been successfully operating Takemaru-kun speech guidance system in Ikoma North community center these four years. We have been also operating two speech guidance systems in local railway station this one year, to study about noisy condition. The collected speech database with the transcription is useful to develop speech dialog systems.We also invented a new quiet speech media, Non-Audible Murmur (NAM), which applied to quiet speech recognition and quiet telephone. This invention awarded by IEICE paper prize and Inose award.

研究计划包括以下课题： 1．降噪信号处理、精确音素建模、说话人和环境适应。2．用于接受自发话语的任务适应语言模型。 3．免提语音识别接口。4．语音对话系统的人为因素研究。这些研究是基于现实世界的语音对话系统进行的。主要研究成果总结如下： 1．开发了基于任意话语的无监督说话人自适应算法，该算法仅需几秒钟，并且显示出与基于50个话语的有监督自适应MLLR几乎相同的精度。 2．使用竹丸君两年的转录文本，为儿童和成人开发了适应任务的语言模型。通过引入针对儿童和成人的并行解码，我们实现了单词准确率和响应准确率的提高。 3．基于零波束形成器类型 SSA（空间减法阵列）和 BSSA（盲 SSA）以及 SIMO-ICA.4 实现了免提语音识别。这四年来，我们在生驹北社区中心成功运营了竹丸君语音引导系统。今年我们还在当地火车站运行了两个语音引导系统，以研究噪声情况。收集到的带有转录的语音数据库对于开发语音对话系统很有用。我们还发明了一种新的安静语音媒体——非可听杂音(NAM)，它应用于安静语音识别和安静电话。该发明荣获IEICE论文奖和Inose奖。

项目成果

期刊论文数量（420）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Two-Stage Blind Source Separation Using SIMO-ICA and Binary Masking

使用 SIMO-ICA 和二进制掩蔽的两级盲源分离

DOI：
发表时间：
2005
期刊：
Proceedings of Joint Workshop on Hands-Free Speech Communication and Microphone Arrays (HSCMA2005)
影响因子：
0
作者：
Hiroshi Saruwatari;Yoshimitsu Mori;Tomoya Takatani;Satoshi Ukai;Kiyohiro Shikano;Takashi Hiekata;Takashi Morita
通讯作者：
Takashi Morita

Blind source separation based on a fast-convergence algorithm combining ICA and beamforming