1 citations · 2 across the 9 of their papers we have counts for
10 papers
HARP: Harmonic-Aware Residual Partitioning for Neural Audio Codecs
Qiaoyu Yang, Lixing He, Binyue Deng +1
Neural audio codecs with residual vector quantization (RVQ) normally treat all frequencies uniformly, so their codebooks become spectrally entangled. Truncating stages then removes…
Poly-SVC: Polyphony-Aware Singing Voice Conversion with Harmonic Modeling
Chen Geng, Meng Chen, Ruohua Zhou +2
Singing Voice Conversion (SVC) aims to transform a source singing voice into a target singer while preserving lyrics and melody. Most existing SVC methods depend on F0 extractors t…
VITA-QinYu: Expressive Spoken Language Model for Role-Playing and Singing
Jiacheng Xu, Heting Gao, Liufei Xie +8
Human speech conveys expressiveness beyond linguistic content, including personality, mood, or performance elements, such as a comforting tone or humming a song, which we formalize…
LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation
Qi Wang, Zhexu Shen, Meng Chen +4
Vocal-to-accompaniment (V2A) generation, which aims to transform a raw vocal recording into a fully arranged accompaniment, inherently requires jointly addressing an accompaniment…
TQCodec: Towards neural audio codec for high-fidelity music streaming
Lixing He, Zhouxuan Chen, Mingshuai Liu +6
We propose TQCodec, a neural audio codec designed for high-bitrate, high-fidelity music streaming. Unlike existing neural codecs that primarily target ultra-low bitrates (<= 16kbps…
Deep Dubbing: End-to-End Auto-Audiobook System with Text-to-Timbre and Context-Aware Instruct-TTS
Ziqi Dai, Yiting Chen, Jiacheng Xu +8
The pipeline for multi-participant audiobook production primarily consists of three stages: script analysis, character voice timbre selection, and speech synthesis. Among these, sc…
CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Ziqi Liang, Xulong Zhang, Chang Liu +3
Voice Conversion (VC) aims to convert the style of a source speaker, such as timbre and pitch, to the style of any target speaker while preserving the linguistic content. However,…
VITS-based Singing Voice Conversion System with DSPGAN post-processing for SVCC2023
Yiquan Zhou, Meng Chen, Yi Lei +2
This paper presents the T02 team's system for the Singing Voice Conversion Challenge 2023 (SVCC2023). Our system entails a VITS-based SVC model, incorporating three modules: a feat…
MBTFNet: Multi-Band Temporal-Frequency Neural Network For Singing Voice Enhancement
Weiming Xu, Zhouxuan Chen, Zhili Tan +5
A typical neural speech enhancement (SE) approach mainly handles speech and noise mixtures, which is not optimal for singing voice enhancement scenarios. Music source separation (M…
KaraTuner: Towards end to end natural pitch correction for singing voice in karaoke
Xiaobin Zhuang, Huiran Yu, Weifeng Zhao +2
An automatic pitch correction system typically includes several stages, such as pitch extraction, deviation estimation, pitch shift processing, and cross-fade smoothing. However, d…