9 papers · 1 filter
POTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text Translation
Xuanchen Li, Chenrui Cui, Tianrui Wang +9
Speech Large Language Models have achieved breakthroughs in multilingual speech-to-text translation. However, existing approaches often overlook semantic commonalities across sourc…
Learning Time-Graph Frequency Representation for Monaural Speech Enhancement
Tingting Wang, Tianrui Wang, Meng Ge +2
The Graph Fourier Transform (GFT) has recently demonstrated promising results in speech enhancement. However, existing GFT-based speech enhancement approaches often employ fixed gr…
LORT: Locally Refined Convolution and Taylor Transformer for Monaural Speech Enhancement
Junyu Wang, Zizhen Lin, Tianrui Wang +3
Achieving superior enhancement performance while maintaining a low parameter count and computational complexity remains a challenge in the field of speech enhancement. In this pape…
Pay More Attention To Audio: Mitigating Imbalance of Cross-Modal Attention in Large Audio Language Models
Junyu Wang, Ziyang Ma, Zhengding Luo +4
Large Audio-Language Models (LALMs) often suffer from audio-textual attention imbalance, prioritizing text over acoustic information, particularly in the multi-modal fusion layers…
Word-Level Emotional Expression Control in Zero-Shot Text-to-Speech Synthesis
Tianrui Wang, Haoyu Wang, Meng Ge +10
While emotional text-to-speech (TTS) has made significant progress, most existing research remains limited to utterance-level emotional expression and fails to support word-level c…
ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning
Junyu Wang, Tianrui Wang, Meng Ge +2
In recent advancements in audio self-supervised representation learning, the standard Transformer architecture has emerged as the predominant approach, yet its attention mechanism…
Reducing the Gap Between Pretrained Speech Enhancement and Recognition Models Using a Real Speech-Trained Bridging Module
Zhongjian Cui, Chenrui Cui, Tianrui Wang +6
The information loss or distortion caused by single-channel speech enhancement (SE) harms the performance of automatic speech recognition (ASR). Observation addition (OA) is an eff…
Mamba-SEUNet: Mamba UNet for Monaural Speech Enhancement
Junyu Wang, Zizhen Lin, Tianrui Wang +3
In recent speech enhancement (SE) research, transformer and its variants have emerged as the predominant methodologies. However, the quadratic complexity of the self-attention mech…
Efficient Emotion and Speaker Adaptation in LLM-Based TTS via Characteristic-Specific Partial Fine-Tuning
Tianrui Wang, Meng Ge, Cheng Gong +11
While LLM-based TTS models exhibit zero-shot emotion and speaker cloning, their cloning fidelity and pronunciation clarity degrade on unseen domains. Fine-tuning is essential for a…