38 citations · 41 across the 28 of their papers we have counts for
9 papers · 1 filter
Towards Effective and Efficient Non-autoregressive decoders for Conformer and LLM-based ASR using Block-based Attention Mask
Tianzi Wang, Xurong Xie, Zengrui Jin +9
Automatic speech recognition (ASR) systems often rely on autoregressive (AR) Transformer decoder architectures, which limit efficient inference parallelization due to their sequent…
CLEAR: Continuous Latent Autoregressive Modeling for High-quality and Low-latency Speech Synthesis
Chun Yat Wu, Jiajun Deng, Guinan Li +2
Autoregressive (AR) language models have emerged as powerful solutions for zero-shot text-to-speech (TTS) synthesis, capable of generating natural speech from a few seconds of audi…
Exploring Cross-Utterance Speech Contexts for Conformer-Transducer Speech Recognition Systems
Mingyu Cui, Mengzhe Geng, Jiajun Deng +8
This paper investigates four types of cross-utterance speech contexts modeling approaches for streaming and non-streaming Conformer-Transformer (C-T) ASR systems: i) input audio fe…
Regularized Federated Learning for Privacy-Preserving Dysarthric and Elderly Speech Recognition
Tao Zhong, Mengzhe Geng, Shujie Hu +2
Accurate recognition of dysarthric and elderly speech remains challenging to date. While privacy concerns have driven a shift from centralized approaches to federated learning (FL)…
MOPSA: Mixture of Prompt-Experts Based Speaker Adaptation for Elderly Speech Recognition
Chengxi Deng, Xurong Xie, Shujie Hu +10
This paper proposes a novel Mixture of Prompt-Experts based Speaker Adaptation approach (MOPSA) for elderly speech recognition. It allows zero-shot, real-time adaptation to unseen…
Towards LLM-Empowered Fine-Grained Speech Descriptors for Explainable Emotion Recognition
Youjun Chen, Xurong Xie, Haoning Xu +6
This paper presents a novel end-to-end LLM-empowered explainable speech emotion recognition (SER) approach. Fine-grained speech emotion descriptor (SED) features, e.g., pitch, tone…
Effective and Efficient One-pass Compression of Speech Foundation Models Using Sparsity-aware Self-pinching Gates
Haoning Xu, Zhaoqing Li, Youjun Chen +5
This paper presents a novel approach for speech foundation models compression that tightly integrates model pruning and parameter update into a single stage. Highly compact layer-l…
On-the-fly Routing for Zero-shot MoE Speaker Adaptation of Speech Foundation Models for Dysarthric Speech Recognition
Shujie HU, Xurong Xie, Mengzhe Geng +8
This paper proposes a novel MoE-based speaker adaptation framework for foundation models based dysarthric speech recognition. This approach enables zero-shot adaptation and real-ti…
Effective and Efficient Mixed Precision Quantization of Speech Foundation Models
Haoning Xu, Zhaoqing Li, Zengrui Jin +7
This paper presents a novel mixed-precision quantization approach for speech foundation models that tightly integrates mixed-precision learning and quantized model parameter estima…