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How Has Deep Learning Revolutionized Human Language Technology?

机译:深度学习如何彻底改变人体语言技术?

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Communication by voice and text, which we refer to as natural language, is a skill that separates humans from all other species. Only humans possess the complete linguistic package. Since the first computer was invented, it's been our dream to interact with computers using spoken and written words. For decades, machine learning approaches in automatic speech recognition (ASR) and natural language processing (NLP) have been based on shallow models such as Gaussian Mixture Models (GMMs) and hidden Markov models (HMM). These approaches use hand-crafted features and models that attempt to integrate knowledge of speech production, perception and linguistics. We often refer to this knowledge as subject matter expertise. Integration of such knowledge has been a cornerstone of signal processing research for decades.
机译:我们称之为自然语言的语音和文本的通信是将人类与所有其他物种分开的技能。只有人类拥有完整的语言包。自从第一台计算机发明以来,我们是我们的梦想与使用口语和书面文字互动。几十年来,自动语音识别(ASR)和自然语言处理(NLP)中的机器学习方法已经基于浅模型,例如高斯混合模型(GMMS)和隐马尔可夫模型(HMM)。这些方法使用试图整合语音生产,感知和语言学知识的手工制作的功能和模型。我们经常将这种知识称为主题专业知识。这些知识的整合已经是数十年来信号处理研究的基石。

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