Spoken language processing: people versus machines

William S-Y. Wang
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Abstract

Summary form only given. A fundamental challenge we must meet for computers to eventually process spoken language as effectively as humans to capture the immensely rich fund of information we have in our heads that is not in the speech signal. This information is what gives us the ability to supply acoustic cues when these are degraded or missing, or to zero in on one speaker amid a chorus of other voices. While the powerful statistical methods currently used in speech recognition and synthesis have brought some success and useful applications, future progress will depend crucially on a deeper knowledge and greater use of this information. Some of this information is applicable to all languages, and some of it is specific to individual language types. In this discussion, special attention is given to the processing of spoken Chinese.
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口语处理:人与机器
只提供摘要形式。要想让计算机最终像人类一样有效地处理口语,捕捉我们大脑中不包含在语音信号中的海量信息,我们必须面对一个根本性的挑战。这些信息使我们能够在声音退化或缺失时提供声音线索,或者在其他声音的合唱中锁定一个扬声器。虽然目前在语音识别和合成中使用的强大的统计方法已经带来了一些成功和有用的应用,但未来的进展将主要取决于对这些信息的更深入的了解和更广泛的使用。其中一些信息适用于所有语言,而另一些则特定于个别语言类型。在这个讨论中,特别关注汉语口语的处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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