将“自然”放回自然语言处理中
Putting Natural in Natural Language Processing
AI总结：
本文指出NLP过度依赖文本而忽视口语，主张借助深度学习的进展统一语音处理与主流NLP，将口语视为人类交流的主要模式，从而构建更高效、拟人且超越文本模态的系统。
摘要：
人类语言首先是口语，其次才是书面语。然而，文本是语言非常便捷且高效的表示方式，现代文明使其无处不在。因此，NLP领域绝大多数情况下专注于处理书面语而非口语。另一方面，关于口语的研究被孤立在基本独立的语音处理社区中，该社区过度专注于将语音转录为文本。深度学习的最新进展使得语音处理与主流NLP在方法上实现了偶然的趋同。可以说，统一这两个领域的时机已经成熟，并且应该开始认真将口语视为人类交流的主要模式。真正的自然语言处理可以促进与语言科学其余部分的更好整合，并可能催生出更具数据效率、更像人类，且能够超越文本模态进行交流的系统。
英文摘要：
Human language is firstly spoken and only secondarily written. Text, however, is a very convenient and efficient representation of language, and modern civilization has made it ubiquitous. Thus the field of NLP has overwhelmingly focused on processing written rather than spoken language. Work on spoken language, on the other hand, has been siloed off within the largely separate speech processing community which has been inordinately preoccupied with transcribing speech into text. Recent advances in deep learning have led to a fortuitous convergence in methods between speech processing and mainstream NLP. Arguably, the time is ripe for a unification of these two fields, and for starting to take spoken language seriously as the primary mode of human communication. Truly natural language processing could lead to better integration with the rest of language science and could lead to systems which are more data-efficient and more human-like, and which can communicate beyond the textual modality.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
