主题演讲3:语音和语言处理中的加权换能器

M. Riley
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引用次数: 0

摘要

本演讲将描述加权换能器在语音和语言处理中的应用。加权换能器是自动机,其中每个转换都有一个输入标签,一个输出标签和一个权重。它们在语音识别和合成、机器翻译、光学字符识别、模式匹配、字符串处理、机器学习、信息提取和检索等方面具有关键应用。我们简要介绍了该领域的历史,加权有限状态和下推换能器的理论和算法概述,讨论了可用的软件库,描述了语音识别,语音合成,机器翻译和NLP的应用,并简要概述了当前的研究问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Keynote 3: Weighted transducers in speech and language processing
This talk will describe the use of weighted transducers in speech and language processing. Weighted transducers are automata where each transition has an input label, an output label, and a weight. They have key applications in speech recognition and synthesis, machine translation, optical character recognition, pattern matching, string processing, machine learning, information extraction and retrieval among others. We give a brief history of the field, an overview of the theory and algorithms of weighted finite-state and pushdown transducers, a discussion of available software libraries, a description of applications to speech recognition, speech synthesis, machine translation and NLP, and a short overview of current research problems.
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