9 papers
WavCube: Unifying Speech Representation for Understanding and Generation via Semantic-Acoustic Joint Modeling
Guanrou Yang, Tian Tan, Qian Chen +12
Integrating speech understanding and generation is a pivotal step toward building unified speech models. However, the different representations required for these two tasks current…
Say More with Less: Variable-Frame-Rate Speech Tokenization via Adaptive Clustering and Implicit Duration Coding
Rui-Chen Zheng, Wenrui Liu, Hui-Peng Du +6
Existing speech tokenizers typically assign a fixed number of tokens per second, regardless of the varying information density or temporal fluctuations in the speech signal. This u…
Speech Token Prediction via Compressed-to-fine Language Modeling for Speech Generation
Wenrui Liu, Qian Chen, Wen Wang +11
Neural audio codecs, used as speech tokenizers, have demonstrated remarkable potential in the field of speech generation. However, to ensure high-fidelity audio reconstruction, neu…
EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Prompting
Guanrou Yang, Chen Yang, Qian Chen +12
Human speech goes beyond the mere transfer of information; it is a profound exchange of emotions and a connection between individuals. While Text-to-Speech (TTS) models have made h…
Enhancing Expressive Voice Conversion with Discrete Pitch-Conditioned Flow Matching Model
Jialong Zuo, Shengpeng Ji, Minghui Fang +8
This paper introduces PFlow-VC, a conditional flow matching voice conversion model that leverages fine-grained discrete pitch tokens and target speaker prompt information for expre…
Analyzing and Mitigating Inconsistency in Discrete Audio Tokens for Neural Codec Language Models
Wenrui Liu, Zhifang Guo, Jin Xu +4
Building upon advancements in Large Language Models (LLMs), the field of audio processing has seen increased interest in training audio generation tasks with discrete audio token s…
CART: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling
Minghui Fang, Shengpeng Ji, Jialong Zuo +9
Cross-modal retrieval aims to search for instances, which are semantically related to the query through the interaction of different modal data. Traditional solutions utilize a sin…
Prompt-Singer: Controllable Singing-Voice-Synthesis with Natural Language Prompt
Yongqi Wang, Ruofan Hu, Rongjie Huang +6
Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and naturalness, yet they lack the capability to control the style attributes of the synthesized…
AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension
Qian Yang, Jin Xu, Wenrui Liu +8
Recently, instruction-following audio-language models have received broad attention for human-audio interaction. However, the absence of benchmarks capable of evaluating audio-cent…