8 citations · 16 across the 6 of their papers we have counts for
7 papers
Exploiting Cross Domain Acoustic-to-articulatory Inverted Features For Disordered Speech Recognition
Shujie Hu, Shansong Liu, Xurong Xie +6
Articulatory features are inherently invariant to acoustic signal distortion and have been successfully incorporated into automatic speech recognition (ASR) systems for normal spee…
Speaker Adaptation Using Spectro-Temporal Deep Features for Dysarthric and Elderly Speech Recognition
Mengzhe Geng, Xurong Xie, Zi Ye +5
Despite the rapid progress of automatic speech recognition (ASR) technologies targeting normal speech in recent decades, accurate recognition of dysarthric and elderly speech remai…
A Comparative Study on Non-Autoregressive Modelings for Speech-to-Text Generation
Yosuke Higuchi, Nanxin Chen, Yuya Fujita +6
Non-autoregressive (NAR) models simultaneously generate multiple outputs in a sequence, which significantly reduces the inference speed at the cost of accuracy drop compared to aut…
An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition
Xuankai Chang, Takashi Maekaku, Pengcheng Guo +8
Self-supervised pretraining on speech data has achieved a lot of progress. High-fidelity representation of the speech signal is learned from a lot of untranscribed data and shows p…
Streaming End-to-End ASR based on Blockwise Non-Autoregressive Models
Tianzi Wang, Yuya Fujita, Xuankai Chang +1
Non-autoregressive (NAR) modeling has gained more and more attention in speech processing. With recent state-of-the-art attention-based automatic speech recognition (ASR) structure…
Toward Streaming ASR with Non-Autoregressive Insertion-based Model
Yuya Fujita, Tianzi Wang, Shinji Watanabe +1
Neural end-to-end (E2E) models have become a promising technique to realize practical automatic speech recognition (ASR) systems. When realizing such a system, one important issue…