首页> 外文会议>Conference on empirical methods in natural language processing >Invited Speaker: Sharon Goldwater, University of Edinburgh:Towards more universal language technology: unsupervised learning from speech
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Invited Speaker: Sharon Goldwater, University of Edinburgh:Towards more universal language technology: unsupervised learning from speech

机译:特邀演讲者:爱丁堡大学的Sharon Goldwater:迈向更通用的语言技术:无监督的语音学习

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Speech and language processing has advanced enormously in the last decade, with successful applications in machine translation, voice-activated search, and even language-enabled personal assistants. Yet these systems typically still rely on learning from very large quantities of human-annotated data. These resource-intensive methods mean that effective technology is available for only a tiny fraction of the world's 7000 or so languages, mainly those spoken in large rich countries.
机译:在过去的十年中,语音和语言处理取得了巨大的进步,在机器翻译,语音激活搜索甚至具有语言功能的个人助理中都得到了成功的应用。然而,这些系统通常仍然依赖于从大量的人类注释数据中学习。这些资源密集型方法意味着有效的技术仅可用于世界7000多种语言中的一小部分,主要是在富裕国家中使用的语言。

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