Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
Situating Automatic Speech Recognition Development within Communities of Under-heard Language Speakers
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DOI：
10.1145/3544548.3581385
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发表时间：
2023-04
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影响因子：
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通讯作者：
Thomas Reitmaier;E. Wallington;Ondrej Klejch;Nina Markl;Léa-Marie Lam-Yee-Mui;Jennifer Pearson;Matt Jones;P. Bell;Simon Robinson
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文献类型：
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作者：
Thomas Reitmaier;E. Wallington;Ondrej Klejch;Nina Markl;Léa-Marie Lam-Yee-Mui;Jennifer Pearson;Matt Jones;P. Bell;Simon Robinson
在本文中，我们开发的方法，自动语音识别（ASR）的发展，适合的需求和功能的听不到的语言扬声器。我们对人机交互的新贡献是展示社区参与如何使关键的技术和社会问题浮出水面，并为更有效的基于语音的系统提供机会。我们推出了一个定制的技术工具包，并展示了我们如何利用该工具包与未被倾听的语言使用者社区进行互动;通过该互动过程，我们将在社区环境中了解ASR发展的关键方面。该工具包包括（1）一个信息设备，以促进社区感兴趣的主题的口头数据收集，（2）一个移动的应用程序，以创建所收集数据的众包副本，以及（3）演示系统，以展示ASR功能并将研究结果反馈给社区成员。利用我们通过这项研究培养的敏感性，我们提出了一系列挑战，以正统的国家的最先进的方法，以ASR的发展。
In this paper we develop approaches to automatic speech recognition (ASR) development that suit the needs and functions of under-heard language speakers. Our novel contribution to HCI is to show how community-engagement can surface key technical and social issues and opportunities for more effective speech-based systems. We introduce a bespoke toolkit of technologies and showcase how we utilised the toolkit to engage communities of under-heard language speakers; and, through that engagement process, situate key aspects of ASR development in community contexts. The toolkit consists of (1) an information appliance to facilitate spoken-data collection on topics of community interest, (2) a mobile app to create crowdsourced transcripts of collected data, and (3) demonstrator systems to showcase ASR capabilities and to feed back research results to community members. Drawing on the sensibilities we cultivated through this research, we present a series of challenges to the orthodoxy of state-of-the-art approaches to ASR development.