3 citations · 8 across the 17 of their papers we have counts for
12 papers · 1 filter
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…
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…
SPA-SVC: Self-supervised Pitch Augmentation for Singing Voice Conversion
Bingsong Bai, Fengping Wang, Yingming Gao +1
Diffusion-based singing voice conversion (SVC) models have shown better synthesis quality compared to traditional methods. However, in cross-domain SVC scenarios, where there is a…
Retrieval Augmented Generation in Prompt-based Text-to-Speech Synthesis with Context-Aware Contrastive Language-Audio Pretraining
Jinlong Xue, Yayue Deng, Yingming Gao +1
Recent prompt-based text-to-speech (TTS) models can clone an unseen speaker using only a short speech prompt. They leverage a strong in-context ability to mimic the speech prompts,…
Improving Audio Codec-based Zero-Shot Text-to-Speech Synthesis with Multi-Modal Context and Large Language Model
Jinlong Xue, Yayue Deng, Yicheng Han +2
Recent advances in large language models (LLMs) and development of audio codecs greatly propel the zero-shot TTS. They can synthesize personalized speech with only a 3-second speec…
Auffusion: Leveraging the Power of Diffusion and Large Language Models for Text-to-Audio Generation
Jinlong Xue, Yayue Deng, Yingming Gao +1
Recent advancements in diffusion models and large language models (LLMs) have significantly propelled the field of AIGC. Text-to-Audio (TTA), a burgeoning AIGC application designed…
Frame-level emotional state alignment method for speech emotion recognition
Qifei Li, Yingming Gao, Cong Wang +4
Speech emotion recognition (SER) systems aim to recognize human emotional state during human-computer interaction. Most existing SER systems are trained based on utterance-level la…
M2-CTTS: End-to-End Multi-scale Multi-modal Conversational Text-to-Speech Synthesis
Jinlong Xue, Yayue Deng, Fengping Wang +5
Conversational text-to-speech (TTS) aims to synthesize speech with proper prosody of reply based on the historical conversation. However, it is still a challenge to comprehensively…
ECAPA-TDNN for Multi-speaker Text-to-speech Synthesis
Jinlong Xue, Yayue Deng, Yichen Han +3
In recent years, neural network based methods for multi-speaker text-to-speech synthesis (TTS) have made significant progress. However, the current speaker encoder models used in t…