6 citations · 8 across the 5 of their papers we have counts for
5 papers
End-to-End Training for Discrete Token LLM based TTS System
Changfeng Gao, Yong Ren, Jun Yuan +3
Recent state-of-the-art (SOTA) text-to-speech (TTS) systems typically adopt a cascaded pipeline consisting of a speech tokenizer, an autoregressive large language model (LLM), and…
Evaluating and Rewarding LALMs for Expressive Role-Play TTS via Mean Continuation Log-Probability
Yong Ren, Jingbei Li, Haiyang Sun +6
Recent advances in Large Audio Language Models (LALMs) have extended Text-to-Speech (TTS) to interactive role-play scenarios, which demand high expressiveness and strict adherence…
Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Ye Bai, Haonan Chen, Jitong Chen +35
We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regr…
NEST-RQ: Next Token Prediction for Speech Self-Supervised Pre-Training
Minglun Han, Ye Bai, Chen Shen +6
Speech self-supervised pre-training can effectively improve the performance of downstream tasks. However, previous self-supervised learning (SSL) methods for speech, such as HuBERT…
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…