16 citations · 28 across the 9 of their papers we have counts for
8 papers · 1 filter
GLM-TTS Technical Report
Jiayan Cui, Zhihan Yang, Naihan Li +10
This work proposes GLM-TTS, a production-level TTS system designed for efficiency, controllability, and high-fidelity speech generation. GLM-TTS follows a two-stage architecture, c…
Enhancing Spectrogram Realism in Singing Voice Synthesis via Explicit Bandwidth Extension Prior to Vocoder
Runxuan Yang, Kai Li, Guo Chen +1
This paper addresses the challenge of enhancing the realism of vocoder-generated singing voice audio by mitigating the distinguishable disparities between synthetic and real-life r…
A Fast and Lightweight Model for Causal Audio-Visual Speech Separation
Wendi Sang, Kai Li, Runxuan Yang +2
Audio-visual speech separation (AVSS) aims to extract a target speech signal from a mixed signal by leveraging both auditory and visual (lip movement) cues. However, most existing…
Time-Frequency-Based Attention Cache Memory Model for Real-Time Speech Separation
Guo Chen, Kai Li, Runxuan Yang +1
Existing causal speech separation models often underperform compared to non-causal models due to difficulties in retaining historical information. To address this, we propose the T…
SonicSim: A customizable simulation platform for speech processing in moving sound source scenarios
Kai Li, Wendi Sang, Chang Zeng +3
Systematic evaluation of speech separation and enhancement models under moving sound source conditions requires extensive and diverse data. However, real-world datasets often lack…
SPMamba: State-space model is all you need in speech separation
Kai Li, Guo Chen, Runxuan Yang +1
Existing CNN-based speech separation models face local receptive field limitations and cannot effectively capture long time dependencies. Although LSTM and Transformer-based speech…
IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation
Kai Li, Runxuan Yang, Fuchun Sun +1
Recent research has made significant progress in designing fusion modules for audio-visual speech separation. However, they predominantly focus on multi-modal fusion at a single te…
An efficient encoder-decoder architecture with top-down attention for speech separation
Kai Li, Runxuan Yang, Xiaolin Hu
Deep neural networks have shown excellent prospects in speech separation tasks. However, obtaining good results while keeping a low model complexity remains challenging in real-wor…