5 papers
FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation
Feiyu Shen, Fenglong Xie, Junjie Li +13
A unified audio model must recognize and understand linguistic, paralinguistic, and environmental information while supporting speech synthesis and editing. A key challenge is repr…
FireRedTTS3: Unified Speech Generation and Editing with Semantically Enriched Speech Representations
Feiyu Shen, Kun Xie, Yichen Wu +8
Recent continuous autoregressive TTS models operate directly on continuous speech representations, preserving rich acoustic details while leveraging the instruction-following capab…
Comprehend and Talk: Text to Speech Synthesis via Dual Language Modeling
Junjie Cao, Yichen Han, Ruonan Zhang +5
Existing Large Language Model (LLM) based autoregressive (AR) text-to-speech (TTS) systems, while achieving state-of-the-art quality, still face critical challenges. The foundation…
MBCodec:Thorough disentangle for high-fidelity audio compression
Ruonan Zhang, Xiaoyang Hao, Yichen Han +3
High-fidelity neural audio codecs in Text-to-speech (TTS) aim to compress speech signals into discrete representations for faithful reconstruction. However, prior approaches faced…
Quantize More, Lose Less: Autoregressive Generation from Residually Quantized Speech Representations
Yichen Han, Xiaoyang Hao, Keming Chen +25
Text-to-speech (TTS) synthesis has seen renewed progress under the discrete modeling paradigm. Existing autoregressive approaches often rely on single-codebook representations, whi…