13 papers · 1 filter
AUV: Teaching Audio Universal Vector Quantization with Single Nested Codebook
Yushen Chen, Kai Hu, Long Zhou +4
We propose AUV, a unified neural audio codec with a single codebook, which enables a favourable reconstruction of speech and further extends to general audio, including vocal, musi…
SongPrep: A Preprocessing Framework and End-to-end Model for Full-song Structure Parsing and Lyrics Transcription
Wei Tan, Shun Lei, Huaicheng Zhang +6
Artificial Intelligence Generated Content (AIGC) is currently a popular research area. Among its various branches, song generation has attracted growing interest. Despite the abund…
Towards Hallucination-Free Music: A Reinforcement Learning Preference Optimization Framework for Reliable Song Generation
Huaicheng Zhang, Wei Tan, Guangzheng Li +8
Recent advances in audio-based generative language models have accelerated AI-driven lyric-to-song generation. However, these models frequently suffer from content hallucination, p…
DualSpeechLM: Towards Unified Speech Understanding and Generation via Dual Speech Token Modeling with Large Language Models
Yuanyuan Wang, Dongchao Yang, Yiwen Shao +5
Extending pre-trained text Large Language Models (LLMs)'s speech understanding or generation abilities by introducing various effective speech tokens has attracted great attention…
Exploring Speaker Diarization with Mixture of Experts
Gaobin Yang, Maokui He, Shutong Niu +3
In this paper, we propose a novel neural speaker diarization system using memory-aware multi-speaker embedding with sequence-to-sequence architecture (NSD-MS2S), which integrates a…
WAKE: Watermarking Audio with Key Enrichment
Yaoxun Xu, Jianwei Yu, Hangting Chen +5
As deep learning advances in audio generation, challenges in audio security and copyright protection highlight the need for robust audio watermarking. Recent neural network-based m…
Controllable Text-to-Speech Synthesis with Masked-Autoencoded Style-Rich Representation
Yongqi Wang, Chunlei Zhang, Hangting Chen +2
Controllable TTS models with natural language prompts often lack the ability for fine-grained control and face a scarcity of high-quality data. We propose a two-stage style-control…
SongBloom: Coherent Song Generation via Interleaved Autoregressive Sketching and Diffusion Refinement
Chenyu Yang, Shuai Wang, Hangting Chen +3
Generating music with coherent structure, harmonious instrumental and vocal elements remains a significant challenge in song generation. Existing language models and diffusion-base…
LeVo: High-Quality Song Generation with Multi-Preference Alignment
Shun Lei, Yaoxun Xu, Zhiwei Lin +10
Recent advances in large language models (LLMs) and audio language models have significantly improved music generation, particularly in lyrics-to-song generation. However, existing…
Layer-wise Investigation of Large-Scale Self-Supervised Music Representation Models
Yizhi Zhou, Haina Zhu, Hangting Chen
Recently, pre-trained models for music information retrieval based on self-supervised learning (SSL) are becoming popular, showing success in various downstream tasks. However, 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…
SongEditor: Adapting Zero-Shot Song Generation Language Model as a Multi-Task Editor
Chenyu Yang, Shuai Wang, Hangting Chen +7
The emergence of novel generative modeling paradigms, particularly audio language models, has significantly advanced the field of song generation. Although state-of-the-art models…
MuQ: Self-Supervised Music Representation Learning with Mel Residual Vector Quantization
Haina Zhu, Yizhi Zhou, Hangting Chen +6
Recent years have witnessed the success of foundation models pre-trained with self-supervised learning (SSL) in various music informatics understanding tasks, including music taggi…