# RyanSpeech: A Corpus for Conversational Text-to-Speech Synthesis

arXiv: https://arxiv.org/abs/2106.08468 · HTML: https://mlsanity.com/paper/2106.08468/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 27 references that are in the map.
- First posted on arXiv 15 Jun 2021.

## Builds on (most cited first, 10 of 10)

- [Conformer: Convolution-augmented Transformer for Speech Recognition](https://mlsanity.com/paper/2005.08100/) (2020)
- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://mlsanity.com/paper/2006.04558/) (2020)
- [LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech](https://mlsanity.com/paper/1904.02882/) (2019)
- [Tacotron: Towards End-to-End Speech Synthesis](https://mlsanity.com/paper/1703.10135/) (2017)
- [Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram](https://mlsanity.com/paper/1910.11480/) (2019)
- [Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset](https://mlsanity.com/paper/1909.05358/) (2019)
- [The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines](https://mlsanity.com/paper/1803.10609/) (2018)
- [ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit](https://mlsanity.com/paper/1910.10909/) (2019)
- [Delivering Cognitive Behavioral Therapy Using A Conversational SocialRobot](https://mlsanity.com/paper/1909.06670/) (2019)

## Built on by (most cited first, 10 of 10)

- [A Survey on Neural Speech Synthesis](https://mlsanity.com/paper/2106.15561/) (2021)
- [Machine Learning for Synthetic Data Generation: A Review](https://mlsanity.com/paper/2302.04062/) (2023)
- [Generative Expressive Conversational Speech Synthesis](https://mlsanity.com/paper/2407.21491/) (2024)
- [Building African Voices](https://mlsanity.com/paper/2207.00688/) (2022)
- [Prosody-controllable spontaneous TTS with neural HMMs](https://mlsanity.com/paper/2211.13533/) (2022)
- [Inclusivity of AI Speech in Healthcare: A Decade Look Back](https://mlsanity.com/paper/2505.10596/) (2025)
- [Multi-Purpose NLP Chatbot : Design, Methodology & Conclusion](https://mlsanity.com/paper/2310.08977/) (2023)
- [SpeechDialogueFactory: Generating High-Quality Speech Dialogue Data to Accelerate Your Speech-LLM Development](https://mlsanity.com/paper/2503.23848/) (2025)
- [Latent Optimal Paths by Gumbel Propagation for Variational Bayesian Dynamic Programming](https://mlsanity.com/paper/2306.02568/) (2023)
- [Let Me Look at You: Advanced Facial Expression Modeling for Conversational Speech Synthesis](https://mlsanity.com/paper/2607.24430/) (2026)

## Abstract (arXiv)

This paper introduces RyanSpeech, a new speech corpus for research on automated text-to-speech (TTS) systems. Publicly available TTS corpora are often noisy, recorded with multiple speakers, or lack quality male speech data. In order to meet the need for a high quality, publicly available male speech corpus within the field of speech recognition, we have designed and created RyanSpeech which contains textual materials from real-world conversational settings. These materials contain over 10 hours of a professional male voice actor's speech recorded at 44.1 kHz. This corpus's design and pipeline make RyanSpeech ideal for developing TTS systems in real-world applications. To provide a baseline for future research, protocols, and benchmarks, we trained 4 state-of-the-art speech models and a vocoder on RyanSpeech. The results show 3.36 in mean opinion scores (MOS) in our best model. We have made both the corpus and trained models for public use.