9 citations · 12 across the 8 of their papers we have counts for
9 papers
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…
MELA-TTS: Joint transformer-diffusion model with representation alignment for speech synthesis
Keyu An, Zhiyu Zhang, Changfeng Gao +7
This work introduces MELA-TTS, a novel joint transformer-diffusion framework for end-to-end text-to-speech synthesis. By autoregressively generating continuous mel-spectrogram fram…
Fun-ASR Technical Report
Keyu An, Yanni Chen, Zhigao Chen +35
In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling, model size scaling, and deep in…
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…
Are Transformers in Pre-trained LM A Good ASR Encoder? An Empirical Study
Keyu An, Shiliang Zhang, Zhijie Yan
In this study, we delve into the efficacy of transformers within pre-trained language models (PLMs) when repurposed as encoders for Automatic Speech Recognition (ASR). Our underlyi…
Paraformer-v2: An improved non-autoregressive transformer for noise-robust speech recognition
Keyu An, Zerui Li, Zhifu Gao +1
Attention-based encoder-decoder, e.g. transformer and its variants, generates the output sequence in an autoregressive (AR) manner. Despite its superior performance, AR model is co…
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…
Advancing VAD Systems Based on Multi-Task Learning with Improved Model Structures
Lingyun Zuo, Keyu An, Shiliang Zhang +1
In a speech recognition system, voice activity detection (VAD) is a crucial frontend module. Addressing the issues of poor noise robustness in traditional binary VAD systems based…