1 citations · 4 across the 18 of their papers we have counts for
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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…
From Reliable Text to Real Voices: Trust-Aware Progressive Adaptation for Low-Resource TTS
Jiayi Lu, Yizhong Geng, Jinghan Yang +4
Low-resource text-to-speech (TTS) adaptation is constrained by scarce paired data and costly manual transcription. Existing fixed-voice TTS systems can provide relatively accurate…
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…
SceneTTS-Bench: A Benchmark for Scene-Level TTS in Drama Dubbing
Yizhong Geng, Yanliang Li, Jinghan Yang +3
Text-to-speech systems are increasingly used for drama dubbing, yet evaluation protocols remain sentence-level, leaving critical scene-level behaviors insufficiently measured. We p…
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…
Hello-Chat: Towards Realistic Social Audio Interactions
Yueran Hou, Peilei Jia, Zihan Sun +5
Recent advancements in Large Audio Language Models (LALMs) have demonstrated exceptional performance in speech recognition and translation. However, existing models often suffer fr…