60 citations · 297 across the 17 of their papers we have counts for
6 papers · 1 filter
Speech-Aware Long Context Pruning and Integration for Contextualized Automatic Speech Recognition
Yiming Rong, Yixin Zhang, Ziyi Wang +5
Automatic speech recognition (ASR) systems have achieved remarkable performance in common conditions but often struggle to leverage long-context information in contextualized scena…
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection
Minglun Han, Linhao Dong, Zhenlin Liang +4
Nowadays, most methods in end-to-end contextual speech recognition bias the recognition process towards contextual knowledge. Since all-neural contextual biasing methods rely on ph…
Efficiently Fusing Pretrained Acoustic and Linguistic Encoders for Low-resource Speech Recognition
Cheng Yi, Shiyu Zhou, Bo Xu
End-to-end models have achieved impressive results on the task of automatic speech recognition (ASR). For low-resource ASR tasks, however, labeled data can hardly satisfy the deman…
Applying Wav2vec2.0 to Speech Recognition in Various Low-resource Languages
Cheng Yi, Jianzhong Wang, Ning Cheng +2
There are several domains that own corresponding widely used feature extractors, such as ResNet, BERT, and GPT-x. These models are usually pre-trained on large amounts of unlabeled…
CIF-based Collaborative Decoding for End-to-end Contextual Speech Recognition
Minglun Han, Linhao Dong, Shiyu Zhou +1
End-to-end (E2E) models have achieved promising results on multiple speech recognition benchmarks, and shown the potential to become the mainstream. However, the unified structure…
Speaker-aware speech-transformer
Zhiyun Fan, Jie Li, Shiyu Zhou +1
Recently, end-to-end (E2E) models become a competitive alternative to the conventional hybrid automatic speech recognition (ASR) systems. However, they still suffer from speaker mi…