most citedNeural Codec Language Models are Zero-Shot Text to Speech Synthesizers

163 citations · 259 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2023★ 17 cited

VioLA: Unified Codec Language Models for Speech Recognition, Synthesis, and Translation

Tianrui Wang, Long Zhou, Ziqiang Zhang +6

Recent research shows a big convergence in model architecture, training objectives, and inference methods across various tasks for different modalities. In this paper, we propose V…

cs.CL2023★ 25 cited

Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language Modeling

Ziqiang Zhang, Long Zhou, Chengyi Wang +10

We propose a cross-lingual neural codec language model, VALL-E X, for cross-lingual speech synthesis. Specifically, we extend VALL-E and train a multi-lingual conditional codec lan…

cs.CL2023★ 163 cited

Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

Chengyi Wang, Sanyuan Chen, Yu Wu +10

We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called Vall-E) using discrete codes derived from…

eess.AS2022★ 36 cited

VATLM: Visual-Audio-Text Pre-Training with Unified Masked Prediction for Speech Representation Learning

Qiushi Zhu, Long Zhou, Ziqiang Zhang +7

Although speech is a simple and effective way for humans to communicate with the outside world, a more realistic speech interaction contains multimodal information, e.g., vision, t…

cs.SD2022★ 2 cited

Joint Pre-Training with Speech and Bilingual Text for Direct Speech to Speech Translation

Kun Wei, Long Zhou, Ziqiang Zhang +5

Direct speech-to-speech translation (S2ST) is an attractive research topic with many advantages compared to cascaded S2ST. However, direct S2ST suffers from the data scarcity probl…

cs.CL2022★ 3 cited

SpeechUT: Bridging Speech and Text with Hidden-Unit for Encoder-Decoder Based Speech-Text Pre-training

Ziqiang Zhang, Long Zhou, Junyi Ao +4

The rapid development of single-modal pre-training has prompted researchers to pay more attention to cross-modal pre-training methods. In this paper, we propose a unified-modal spe…

cs.CL2022★ 13 cited

SpeechLM: Enhanced Speech Pre-Training with Unpaired Textual Data

Ziqiang Zhang, Sanyuan Chen, Long Zhou +8

How to boost speech pre-training with textual data is an unsolved problem due to the fact that speech and text are very different modalities with distinct characteristics. In this…

cs.SD2022

Pre-Training Transformer Decoder for End-to-End ASR Model with Unpaired Speech Data

Junyi Ao, Ziqiang Zhang, Long Zhou +7

This paper studies a novel pre-training technique with unpaired speech data, Speech2C, for encoder-decoder based automatic speech recognition (ASR). Within a multi-task learning fr…