Industrial Research into ASR Bias'

这项研究将专注于减少基础自动语音识别(ASR)服务(如OpenAI的Whisper)中的偏见。这项研究的目的是为了减少英国少数语言群体在建议提供环境中的ASR偏见。这项研究源于我们对英国口音ASR基础模型中的偏见的识别。我们的目标是通过现在和未来了解什么是减少这种偏见的最有效方法来进一步发展这项研究。这里我们关注的是提供建议的设置，但这项工作将转移到ASR的其他用途，如个人助理或其他对话设置，如客户服务。通过减轻这些基础ASR服务中的偏见，本研究为更公平的人工智能铺平了道路，人工智能更具社会责任感，更值得信赖，因此被广泛采用。

This research will focus on reducing biases in foundational Automatic Speech Recognition (ASR) services (e.g. OpenAI's Whisper). The aim is to reduce ASR biases for minority linguistic groups in UK advice giving settings.This research follows on from our identification of bias in foundational ASR models for UK accents. Our aim is to further develop this research by now focusing on understanding what is the most efficient method to reduce this bias now and in the future. Here we focus on advice giving settings, but this work will transfer to other uses of ASRs such as personal assistants or other conversational settings e.g. customer service.By mitigating the biases in these foundation ASR services this research paves the way for more equitable AI, AI that is more socially responsible, trustworthy, and therefore widely adopted.