3 citations · 8 across the 17 of their papers we have counts for
8 papers · 1 filter
SemiCodec: Bridging Speech Tokenization and High-fidelity Reconstruction with Semi-discrete Representations
Kecan Mao, Nan Xu, Zhaoyang Meng +4
Speech representation learning requires a discrete modeling interface while preserving high waveform fidelity. Existing approaches rarely achieve both: discrete tokens ease modelin…
VoTSpeech: Decoupling Voice Design from Speech Generation in Instruction-Following TTS
Wenbing Yang, Qihang Lu, Zihan Sun +4
Instruction-following text-to-speech (TTS) typically leaves voice design implicit, as conventional speaker embeddings encode reference audio rather than text-driven targets. We pro…
Stabilizing Instruction Supervision for Instruct-TTS via Controllable Diversification and Drift Filtering
Yizhong Geng, Kecan Mao, Qifei Li +6
Instruct-TTS systems expand structured style labels into natural-language training instructions through LLM rewriting, yet we find that over 40% of unconstrained rewrites contain s…
CLASVS: Continuous-Latent Autoregression for Melody-Preserving Lyric Editing in Singing Voice Synthesis
Yizhong Geng, Tian-Hao Zhang, Chunfeng Wang +7
Reference-conditioned melody-preserving lyric editing replaces words while retaining a performance's timing, singer identity, and naturalness. Continuous-latent autoregression avoi…
MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis
Yuhua Wen, Yingying Zhou, Qifei Li +4
Most existing multimodal sentiment analysis approaches assume access to complete multimodal inputs. However, real-world applications frequently encounter incomplete or corrupted mo…
MeloCodec: Harnessing Melodic Priors for High-Fidelity Singing Voice Representation
Yizhong Geng, Wenxin Fu, Kecan Mao +7
Neural audio codecs serve as fundamental tokenizers for LLM-based audio generation. While semantic priors are widely exploited to enhance linguistic intelligibility, the integratio…
AffectCodec: Emotion-Preserving Neural Speech Codec with Block-Diagonal Residual FSQ
Zhaoyang Meng, Zhengyao Ma, Kecan Mao +2
Neural speech codecs have become the discrete interface between raw audio and speech language models, yet they remain optimized primarily for acoustic reconstruction fidelity, whic…
Bridging the Stability-Expressivity Gap: Synthetic Data Scaling and Preference Alignment for Low-Resource Spoken Language Models
Yizhong Geng, Yanliang Li, Jinghan Yang +4
Spoken Language Models (SLMs) have emerged as a promising paradigm for speech synthesis by bypassing explicit grapheme-to-phoneme pipelines. However, their effectiveness in low-res…