梳理SQA领域挑战与开源工具，推动语音生成评估发展
Advancing Speech Quality Assessment Through Scientific Challenges and Open-source Activities
- 回顾近年SQA科学挑战与开源实现
- 强调自动评估在语音生成中的严谨性作用
- 适合语音生成与评估研究者参考
语音质量评估（SQA）旨在衡量语音质量，开发能反映人类感知的精准自动SQA方法，对于跟上生成式AI的发展至关重要。近年来，SQA已进步到研究人员可将其作为论文中语音生成系统优劣的严格度量标准。我们认为，近期的科学挑战与开源活动促进了该领域的发展。本文综述了近期的挑战以及SQA的开源实现和工具包，并强调持续开展此类活动对推进SQA及语音生成式AI的重要性。
原文摘要 · Abstract (English)
Speech quality assessment (SQA) refers to the evaluation of speech quality, and developing an accurate automatic SQA method that reflects human perception has become increasingly important, in order to keep up with the generative AI boom. In recent years, SQA has progressed to a point that researchers started to faithfully use automatic SQA in research papers as a rigorous measurement of goodness for speech generation systems. We believe that the scientific challenges and open-source activities of late have stimulated the growth in this field. In this paper, we review recent challenges as well as open-source implementations and toolkits for SQA, and highlight the importance of maintaining such activities to facilitate the development of not only SQA itself but also generative AI for speech.
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