Large self-supervised pre-trained speech models require computationally
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In this paper, we propose ACA-Net, a lightweight, global context-aware
s...
Most of the existing neural-based models for keyword spotting (KWS) in s...
Existing self-supervised pre-trained speech models have offered an effec...
Noise robustness in keyword spotting remains a challenge as many models ...
Transformer models have been used in automatic speech recognition (ASR)
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In this work, we study leveraging extra text data to improve low-resourc...
The attention-based end-to-end (E2E) automatic speech recognition (ASR)
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The lack of code-switch training data is one of the major concerns in th...