10 papers · 1 filter
Towards Data-free and Training-free Compression for Speech Foundation Models Using Parameter Clustering
Haoning Xu, Zhaoqing Li, Huimeng Wang +4
This paper presents a novel data-free and training-free compression approach for speech foundation models using channelwise clustering via k-means. More fine-grained, mixed sparsit…
Multi-Channel Speech Enhancement for Cocktail Party Speech Emotion Recognition
Youjun Chen, Guinan Li, Mengzhe Geng +9
This paper highlights the critical importance of multi-channel speech enhancement (MCSE) for speech emotion recognition (ER) in cocktail party scenarios. A multi-channel speech der…
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…
Towards One-bit ASR: Extremely Low-bit Conformer Quantization Using Co-training and Stochastic Precision
Zhaoqing Li, Haoning Xu, Zengrui Jin +7
Model compression has become an emerging need as the sizes of modern speech systems rapidly increase. In this paper, we study model weight quantization, which directly reduces the…
Unfolding A Few Structures for The Many: Memory-Efficient Compression of Conformer and Speech Foundation Models
Zhaoqing Li, Haoning Xu, Xurong Xie +3
This paper presents a novel memory-efficient model compression approach for Conformer ASR and speech foundation systems. Our approach features a unique "small-to-large" design. A c…
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…
Phone-purity Guided Discrete Tokens for Dysarthric Speech Recognition
Huimeng Wang, Xurong Xie, Mengzhe Geng +6
Discrete tokens extracted provide efficient and domain adaptable speech features. Their application to disordered speech that exhibits articulation imprecision and large mismatch a…
Homogeneous Speaker Features for On-the-Fly Dysarthric and Elderly Speaker Adaptation
Mengzhe Geng, Xurong Xie, Jiajun Deng +7
The application of data-intensive automatic speech recognition (ASR) technologies to dysarthric and elderly adult speech is confronted by their mismatch against healthy and nonaged…
One-pass Multiple Conformer and Foundation Speech Systems Compression and Quantization Using An All-in-one Neural Model
Zhaoqing Li, Haoning Xu, Tianzi Wang +7
We propose a novel one-pass multiple ASR systems joint compression and quantization approach using an all-in-one neural model. A single compression cycle allows multiple nested sys…
Towards Effective and Efficient Non-autoregressive Decoding Using Block-based Attention Mask
Tianzi Wang, Xurong Xie, Zhaoqing Li +9
This paper proposes a novel non-autoregressive (NAR) block-based Attention Mask Decoder (AMD) that flexibly balances performance-efficiency trade-offs for Conformer ASR systems. AM…