# Voice Conversion by Cascading Automatic Speech Recognition and Text-to-Speech Synthesis with Prosody Transfer

arXiv: https://arxiv.org/abs/2009.01475 · HTML: https://mlsanity.com/paper/2009.01475/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Sep 2020.

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

- [A Large-Scale Evaluation of Speech Foundation Models](https://mlsanity.com/paper/2404.09385/) (2024)
- [S3PRL-VC: Open-source Voice Conversion Framework with Self-supervised Speech Representations](https://mlsanity.com/paper/2110.06280/) (2021)
- [Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniques](https://mlsanity.com/paper/2104.00931/) (2021)
- [NVC-Net: End-to-End Adversarial Voice Conversion](https://mlsanity.com/paper/2106.00992/) (2021)
- [A Comparative Study of Self-supervised Speech Representation Based Voice Conversion](https://mlsanity.com/paper/2207.04356/) (2022)
- [On Prosody Modeling for ASR+TTS based Voice Conversion](https://mlsanity.com/paper/2107.09477/) (2021)
- [Improved Prosodic Clustering for Multispeaker and Speaker-independent Phoneme-level Prosody Control](https://mlsanity.com/paper/2111.10168/) (2021)
- [GlowVC: Mel-spectrogram space disentangling model for language-independent text-free voice conversion](https://mlsanity.com/paper/2207.01454/) (2022)
- [Multilingual Prosody Transfer: Comparing Supervised & Transfer Learning](https://mlsanity.com/paper/2406.00022/) (2024)
- [Low-Latency Real-Time Non-Parallel Voice Conversion based on Cyclic Variational Autoencoder and Multiband WaveRNN with Data-Driven Linear Prediction](https://mlsanity.com/paper/2105.09858/) (2021)

## Abstract (arXiv)

With the development of automatic speech recognition (ASR) and text-to-speech synthesis (TTS) technique, it's intuitive to construct a voice conversion system by cascading an ASR and TTS system. In this paper, we present a ASR-TTS method for voice conversion, which used iFLYTEK ASR engine to transcribe the source speech into text and a Transformer TTS model with WaveNet vocoder to synthesize the converted speech from the decoded text. For the TTS model, we proposed to use a prosody code to describe the prosody information other than text and speaker information contained in speech. A prosody encoder is used to extract the prosody code. During conversion, the source prosody is transferred to converted speech by conditioning the Transformer TTS model with its code. Experiments were conducted to demonstrate the effectiveness of our proposed method. Our system also obtained the best naturalness and similarity in the mono-lingual task of Voice Conversion Challenge 2020.