1.9k citations · 3k across the 49 of their papers we have counts for
6 papers · 2 filters
Boosting Large Language Model for Speech Synthesis: An Empirical Study
Hongkun Hao, Long Zhou, Shujie Liu +4
Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as spee…
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…
ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation
Chenyang Le, Yao Qian, Long Zhou +4
Joint speech-language training is challenging due to the large demand for training data and GPU consumption, as well as the modality gap between speech and language. We present Com…
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…
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
Eric Sun, Jinyu Li, Yuxuan Hu +8
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users dur…
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…