This paper addresses the challenges and advancements in speech recognition
for singing, a domain distinctly different from standard speech recognition.
Singing encompasses unique challenges, including extensive pitch variations,
diverse vocal styles, and background music interference. We explore key areas
such as phoneme recognition, language identification in songs, keyword
spotting, and full lyrics transcription. I will describe some of my own
experiences when performing research on these tasks just as they were starting
to gain traction, but will also show how recent developments in deep learning
and large-scale datasets have propelled progress in this field. My goal is to
illuminate the complexities of applying speech recognition to singing, evaluate
current capabilities, and outline future research directions.

本文旨在探讨歌唱领域中的语音识别挑战和进展，包括音高变化、各种歌唱风格和背景音乐干扰等唱歌所特有的挑战。我们研究了音素识别、歌曲中的语言识别、关键词检测和完整歌词转写等关键领域。通过描述作者在这些任务刚开始崭露头角的研究经历，同时还介绍了近期深度学习和大规模数据集方面的新进展如何推动了该领域的进步。本文的目标是阐明将语音识别技术应用于歌唱中的复杂性，评估当前的能力，并提出未来的研究方向。