5 papers · 1 filter
Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering
Junyu Dai, Xinyue Fan, Weiqin Li +14
In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and musical attributes. The propo…
AutoStyle-TTS: Retrieval-Augmented Generation based Automatic Style Matching Text-to-Speech Synthesis
Dan Luo, Chengyuan Ma, Weiqin Li +3
With the advancement of speech synthesis technology, users have higher expectations for the naturalness and expressiveness of synthesized speech. But previous research ignores the…
UniSep: Universal Target Audio Separation with Language Models at Scale
Yuanyuan Wang, Hangting Chen, Dongchao Yang +7
We propose Universal target audio Separation (UniSep), addressing the separation task on arbitrary mixtures of different types of audio. Distinguished from previous studies, UniSep…
The Codec Language Model-based Zero-Shot Spontaneous Style TTS System for CoVoC Challenge 2024
Shuoyi Zhou, Yixuan Zhou, Weiqin Li +6
This paper describes the zero-shot spontaneous style TTS system for the ISCSLP 2024 Conversational Voice Clone Challenge (CoVoC). We propose a LLaMA-based codec language model with…
Spontaneous Style Text-to-Speech Synthesis with Controllable Spontaneous Behaviors Based on Language Models
Weiqin Li, Peiji Yang, Yicheng Zhong +5
Spontaneous style speech synthesis, which aims to generate human-like speech, often encounters challenges due to the scarcity of high-quality data and limitations in model capabili…