# DiDiSpeech: A Large Scale Mandarin Speech Corpus

arXiv: https://arxiv.org/abs/2010.09275 · HTML: https://mlsanity.com/paper/2010.09275/

## Key facts

- Cited by 33 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Oct 2020.

## Built on by (most cited first, 30 of 33)

- [F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching](https://mlsanity.com/paper/2410.06885/) (2024)
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- [MaskGCT: Zero-Shot Text-to-Speech with Masked Generative Codec Transformer](https://mlsanity.com/paper/2409.00750/) (2024)
- [IndexTTS2: A Breakthrough in Emotionally Expressive and Duration-Controlled Auto-Regressive Zero-Shot Text-to-Speech](https://mlsanity.com/paper/2506.21619/) (2025)
- [DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation](https://mlsanity.com/paper/2502.03930/) (2025)
- [ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching](https://mlsanity.com/paper/2506.13053/) (2025)
- [EMOVIE: A Mandarin Emotion Speech Dataset with a Simple Emotional Text-to-Speech Model](https://mlsanity.com/paper/2106.09317/) (2021)
- [Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition](https://mlsanity.com/paper/2109.09161/) (2021)
- [TaDiCodec: Text-aware Diffusion Speech Tokenizer for Speech Language Modeling](https://mlsanity.com/paper/2508.16790/) (2025)
- [Prompt-Singer: Controllable Singing-Voice-Synthesis with Natural Language Prompt](https://mlsanity.com/paper/2403.11780/) (2024)
- [TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch](https://mlsanity.com/paper/2412.08237/) (2024)
- [Pseudo-Autoregressive Neural Codec Language Models for Efficient Zero-Shot Text-to-Speech Synthesis](https://mlsanity.com/paper/2504.10352/) (2025)
- [DMOSpeech 2: Reinforcement Learning for Duration Prediction in Metric-Optimized Speech Synthesis](https://mlsanity.com/paper/2507.14988/) (2025)
- [Review of end-to-end speech synthesis technology based on deep learning](https://mlsanity.com/paper/2104.09995/) (2021)
- [IndexTTS 2.5 Technical Report](https://mlsanity.com/paper/2601.03888/) (2026)
- [Voice Cloning: Comprehensive Survey](https://mlsanity.com/paper/2505.00579/) (2025)
- [Direct Preference Optimization for Speech Autoregressive Diffusion Models](https://mlsanity.com/paper/2509.18928/) (2025)
- [Bailing-TTS: Chinese Dialectal Speech Synthesis Towards Human-like Spontaneous Representation](https://mlsanity.com/paper/2408.00284/) (2024)
- [VoiceCraft-X: Unifying Multilingual, Voice-Cloning Speech Synthesis and Speech Editing](https://mlsanity.com/paper/2511.12347/) (2025)
- [The NPU-HWC System for the ISCSLP 2024 Inspirational and Convincing Audio Generation Challenge](https://mlsanity.com/paper/2410.23815/) (2024)
- [A Semantic Information-based Hierarchical Speech Enhancement Method Using Factorized Codec and Diffusion Model](https://mlsanity.com/paper/2505.13843/) (2025)
- [FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation](https://mlsanity.com/paper/2608.24168/) (2026)
- [IMaSC -- ICFOSS Malayalam Speech Corpus](https://mlsanity.com/paper/2211.12796/) (2022)
- [Multi-Accent Mandarin Dry-Vocal Singing Dataset: Benchmark for Singing Accent Recognition](https://mlsanity.com/paper/2512.07005/) (2025)
- [DSFlow: Dual Supervision and Step-Aware Architecture for One-Step Flow Matching Speech Synthesis](https://mlsanity.com/paper/2602.09041/) (2026)
- [WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling](https://mlsanity.com/paper/2606.03455/) (2026)
- [UL-UNAS: Ultra-Lightweight U-Nets for Real-Time Speech Enhancement via Network Architecture Search](https://mlsanity.com/paper/2503.00340/) (2025)
- [PoDAR: Power-Disentangled Audio Representation for Generative Modeling](https://mlsanity.com/paper/2605.10084/) (2026)
- [ZONOS2 Technical Report](https://mlsanity.com/paper/2606.24320/) (2026)
- [Faster IndexTTS-2: Accelerating and Streaming Autoregressive Zero-Shot Text-to-Speech Synthesis on GPUs](https://mlsanity.com/paper/2607.21042/) (2026)

## Abstract (arXiv)

This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech. It consists of about 800 hours of speech data at 48kHz sampling rate from 6000 speakers and the corresponding texts. All speech data in the corpus is recorded in quiet environment and is suitable for various speech processing tasks, such as voice conversion, multi-speaker text-to-speech and automatic speech recognition. We conduct experiments with multiple speech tasks and evaluate the performance, showing that it is promising to use the corpus for both academic research and practical application. The corpus is available at https://outreach.didichuxing.com/research/opendata/.