62 citations · 72 across the 4 of their papers we have counts for
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eess.AS2024★ 6 cited
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…
eess.AS2022★ 3 cited
Nextformer: A ConvNeXt Augmented Conformer For End-To-End Speech Recognition
Yongjun Jiang, Jian Yu, Wenwen Yang +2
Conformer models have achieved state-of-the-art(SOTA) results in end-to-end speech recognition. However Conformer mainly focuses on temporal modeling while pays less attention on t…
eess.AS2020★ 62 cited
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…