WenetSpeech4TTS

WenetSpeech4TTS is a multi-domain Mandarin corpus derived from the open-sourced WenetSpeech dataset. Tailored for the text-to-speech tasks, we refined WenetSpeech by adjusting segment boundaries, enhancing the audio quality, and eliminating speaker mixing within each segment. Following a more accurate transcription process and quality-based data filtering process, the obtained WenetSpeech4TTS corpus contains 12,800 hours of paired audio-text data. Furthermore, we have created subsets of varying sizes, categorized by segment quality scores to allow for TTS model training and finetuning.

WenetSpeech4TTS是一款源自开源WenetSpeech数据集的多领域普通话语料库。本语料库专为文本到语音（text-to-speech，TTS）任务定制，我们对原始WenetSpeech数据集进行了优化处理：调整语音片段边界、提升音频质量，并消除各片段内的说话人混叠问题。经更精准的转录流程与基于质量的数据筛选流程后，最终构建的WenetSpeech4TTS语料库包含12800小时的音文配对数据。此外，我们还依据片段质量评分构建了不同规模的子集，以支持文本到语音模型的训练与微调。

搜集汇总

背景与挑战

背景概述

WenetSpeech4TTS是一个专为TTS任务优化的多领域普通话语料库，包含12,800小时的音频-文本配对数据，并根据质量分为多个子集。该数据集源自WenetSpeech，经过优化处理，适用于非商业研究目的，并提供了训练基准和预训练模型。