论文标题
嘿，ASR系统！你为什么不包容？自动语音识别系统的偏见和提出的偏差缓解技术。文献综述
Hey ASR System! Why Aren't You More Inclusive? Automatic Speech Recognition Systems' Bias and Proposed Bias Mitigation Techniques. A Literature Review
论文作者
论文摘要
言语是人类之间交流的基本手段。人工智能和复杂的语音技术的出现导致了基于人类到计算机的互动的快速扩散，这主要是由自动语音识别（ASR）系统促进的。 ASR系统通常以音频的形式采用人类语音并将其转换为单词，但是对于某些用户来说，它无法解码语音，并且任何输出文本都充满了人类读者无法理解的错误。这些系统并不适合所有人，实际上阻碍了某些用户的生产力。在本文中，我们提出的研究解决了ASR偏向性别，种族和病人和残疾人的偏见，同时探索了提出ASR偏见技术来减轻这些歧视的研究。我们还讨论了设计一种更容易访问和包容的ASR技术的技术。对于所调查的每种方法，我们还提供了所采用的调查和方法，所使用的ASR系统和语料库以及研究结果的摘要，并强调了它们的优势和/或劣势。最后，我们为自然语言处理的研究人员提供了未来的机会，可以在ASR技术的下一个级别创建中探索。
Speech is the fundamental means of communication between humans. The advent of AI and sophisticated speech technologies have led to the rapid proliferation of human-to-computer-based interactions, fueled primarily by Automatic Speech Recognition (ASR) systems. ASR systems normally take human speech in the form of audio and convert it into words, but for some users, it cannot decode the speech, and any output text is filled with errors that are incomprehensible to the human reader. These systems do not work equally for everyone and actually hinder the productivity of some users. In this paper, we present research that addresses ASR biases against gender, race, and the sick and disabled, while exploring studies that propose ASR debiasing techniques for mitigating these discriminations. We also discuss techniques for designing a more accessible and inclusive ASR technology. For each approach surveyed, we also provide a summary of the investigation and methods applied, the ASR systems and corpora used, and the research findings, and highlight their strengths and/or weaknesses. Finally, we propose future opportunities for Natural Language Processing researchers to explore in the next level creation of ASR technologies.
