11 papers · 1 filter
AudioCALM: Continuous Autoregressive Language Modeling for Universal Audio Generation
Huadai Liu, Kaicheng Luo, Wen Wang +4
Unifying speech, sound, and music generation in one model is hindered by tradeoffs between fidelity, end-to-end training, in-context conditioning, and variable-length synthesis tha…
STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation
Huadai Liu, Wen Wang, Kaicheng Luo +3
Continuous Variational Autoencoders (VAEs) serve as the fundamental continuous tokenizer for modern neural audio generation systems, enabling high-fidelity reconstruction while pro…
BareWave: Waveform-Native Flow-Matching Text-to-Speech
Wei Fan, Chao-Hong Tan, Qian Chen +5
Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling. In text-to-speech, however, high-quality syst…
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…
ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing
Huadai Liu, Kaicheng Luo, Jialei Wang +4
While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like p…
ControlSpeech: Towards Simultaneous and Independent Zero-shot Speaker Cloning and Zero-shot Language Style Control
Shengpeng Ji, Qian Chen, Wen Wang +8
In this paper, we present ControlSpeech, a text-to-speech (TTS) system capable of fully cloning the speaker's voice and enabling arbitrary control and adjustment of speaking style.…