Representing speech and audio signals in discrete units has become a compelling alternative to traditional high-dimensional feature vectors. Numerous studies have highlighted the efficacy of discrete units in various applications such as speech compression and restoration, speech recognition, and speech generation. To foster exploration in this domain, we introduce the Interspeech 2024 Challenge, which focuses on new speech processing benchmarks using discrete units. It encompasses three pivotal tasks, namely multilingual automatic speech recognition, text-to-speech, and singing voice synthesis, and aims to assess the potential applicability of discrete units in these tasks. This paper outlines the challenge designs and baseline descriptions. We also collate baseline and selected submission systems, along with preliminary findings, offering valuable contributions to future research in this evolving field.

翻译：使用离散单元表示语音和音频信号已成为传统高维特征向量的一种引人注目的替代方案。大量研究已突显了离散单元在语音压缩与恢复、语音识别及语音生成等多种应用中的有效性。为促进该领域的探索，我们推出了Interspeech 2024挑战赛，重点关注使用离散单元的新型语音处理基准测试。该挑战赛涵盖三项关键任务，即多语言自动语音识别、文本到语音转换以及歌声合成，旨在评估离散单元在这些任务中的潜在适用性。本文概述了挑战赛的设计与基线系统描述。我们还汇总了基线系统及部分入选的提交系统，并提供了初步研究结果，为这一快速发展领域的未来研究提供了有价值的参考。