面向柔性语音识别——东京工业大学的最新进展

S. Furui
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引用次数: 8

摘要

本文介绍了东京工业大学的进展,以及作者对语音识别系统在声学和语言处理层面上更加灵活的看法。具体来说,它描述了一个广播新闻转录系统、多模态人机界面、基于神经网络的HMM自适应噪声语音、结合自动说话人变化检测的在线增量说话人自适应、消息驱动的语音识别和理解、日本一个关于自发语音语料库和处理技术的国家项目,以及语音摘要。对于自发语音的处理,从语音识别到理解的范式转换将是必不可少的,从理解中提取说话人的潜在信息,而不是转录所有的口语。建立一个庞大的自发语音语料库来构建可靠的声学和语言学模型也至关重要。主要由于使计算机更小、更强大和更便宜的技术,预计在21世纪的最初几年将出现无处不在和可穿戴的计算时代。在这样的环境下,语音识别将作为人机交互的主要方法之一得到广泛的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward flexible speech recognition-recent progress at Tokyo Institute of Technology
This paper describes the progress at Tokyo Institute of Technology and the author's perspectives for making speech recognition systems more flexible at both the acoustic and linguistic processing levels. Specifically, it describes a broadcast news transcription system, multimodal human-computer interface, neural-network-based HMM adaptation for noisy speech, online incremental speaker adaptation combined with automatic speaker-change detection, message-driven speech recognition and understanding, a Japanese national project on spontaneous speech corpus and processing technology, and speech summarization. For processing spontaneous speech, paradigm shift from speech recognition to understanding where underlying messages of the speaker are extracted will be indispensable, instead of transcribing all the spoken words. Building a large corpus of spontaneous speech to construct reliable acoustic and linguistic models is also crucial. Due principally to the technology of making computers smaller, more powerful and cheaper, the ubiquitous and wearable computing era is expected to come into being in the initial years of the 21st century. In such an environment, speech recognition will be widely used as one of the principal methods of human-computer interaction.
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