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连续语音识别的技术现状。

State of the art in continuous speech recognition.

作者信息

Makhoul J, Schwartz R

机构信息

BBN Systems and Technologies, Cambridge, MA 02138, USA.

出版信息

Proc Natl Acad Sci U S A. 1995 Oct 24;92(22):9956-63. doi: 10.1073/pnas.92.22.9956.

Abstract

In the past decade, tremendous advances in the state of the art of automatic speech recognition by machine have taken place. A reduction in the word error rate by more than a factor of 5 and an increase in recognition speeds by several orders of magnitude (brought about by a combination of faster recognition search algorithms and more powerful computers), have combined to make high-accuracy, speaker-independent, continuous speech recognition for large vocabularies possible in real time, on off-the-shelf workstations, without the aid of special hardware. These advances promise to make speech recognition technology readily available to the general public. This paper focuses on the speech recognition advances made through better speech modeling techniques, chiefly through more accurate mathematical modeling of speech sounds.

摘要

在过去十年中,机器自动语音识别技术取得了巨大进展。单词错误率降低了五倍多,识别速度提高了几个数量级(这是由更快的识别搜索算法和更强大的计算机共同实现的),使得在无需特殊硬件的现成工作站上实时进行高精度、与说话者无关的大词汇量连续语音识别成为可能。这些进展有望使语音识别技术为广大公众所广泛使用。本文重点关注通过更好的语音建模技术取得的语音识别进展,主要是通过对语音进行更精确的数学建模。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4074/40718/871a2e02fda3/pnas01500-0055-a.jpg

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