9 citations · 17 across the 9 of their papers we have counts for
6 papers · 1 filter
RRPO: Robust Reward Policy Optimization for LLM-based Emotional TTS
Cong Wang, Changfeng Gao, Yang Xiang +7
Differentiable reinforcement learning (RL) frameworks like DiffRO offer a powerful approach for controllable text-to-speech (TTS), but are vulnerable to reward hacking, particularl…
Explore the Reinforcement Learning for the LLM based ASR and TTS system
Changfeng Gao, Yabin Li, Keyu An +4
In recent years, large language models (LLMs) have played an important role in automatic speech recognition (ASR) and text-to-speech (TTS) systems. While reinforcement learning (RL…
Differentiable Reward Optimization for LLM based TTS system
Changfeng Gao, Zhihao Du, Shiliang Zhang
This paper proposes a novel Differentiable Reward Optimization (DiffRO) method aimed at enhancing the performance of neural codec language models based text-to-speech (TTS) systems…
CosyVoice 3: Towards In-the-wild Speech Generation via Scaling-up and Post-training
Zhihao Du, Changfeng Gao, Yuxuan Wang +19
In our prior works, we introduced a scalable streaming speech synthesis model, CosyVoice 2, which integrates a large language model (LLM) and a chunk-aware flow matching (FM) model…
CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models
Zhihao Du, Yuxuan Wang, Qian Chen +16
In our previous work, we introduced CosyVoice, a multilingual speech synthesis model based on supervised discrete speech tokens. By employing progressive semantic decoding with two…
FunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs
Keyu An, Qian Chen, Chong Deng +30
This report introduces FunAudioLLM, a model family designed to enhance natural voice interactions between humans and large language models (LLMs). At its core are two innovative mo…