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（例如OpenAI的Whisper）中的偏见。我们的目的是减少在英国的建议给予settings.This研究从我们的识别偏见的基础ASR模型为英国口音的少数语言群体的ASR偏见。我们的目标是进一步发展这项研究，现在专注于了解现在和未来减少这种偏见的最有效方法。在这里，我们专注于提供建议的设置，但这项工作将转移到其他用途的ASR，如个人助理或其他会话设置，如客户服务。通过减轻这些基础ASR服务中的偏见，这项研究为更公平的AI铺平了道路，AI更具社会责任感，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.