9 papers
Spoken Function Calling: A New Perspective on Spoken Language Understanding for Large Audio Language Models
Yuezhang Peng, Yuxin Liu, Changfeng Gao +3
Spoken Language Understanding (SLU) is the core component of task-oriented dialogue systems and a pivotal link in achieving seamless human-agent interaction. While traditional SLU…
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…
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…
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…