arXiv:2110.07498
공식 코드 · Papers with Code
End-to-end Keyword Spotting using Xception-1d
원문 초록
The field of conversational agents is growing fast and there is an increasing need for algorithms that enhance natural interaction. In this work we show how we achieved state of the art results in the Keyword Spotting field by adapting and tweaking the Xception algorithm, which achieved outstanding results in several computer vision tasks. We obtained about 96\% accuracy when classifying audio clips belonging to 35 different categories, beating human annotation at the most complex tasks proposed.
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Advances in Small-Footprint Keyword Spotting: A Comprehensive Review of Efficient Models and Algorithms
GLAP: General contrastive audio-text pretraining across domains and languages
Chameleon: A MatMul-Free Temporal Convolutional Network Accelerator for End-to-End Few-Shot and Continual Learning from Sequential Data
MFA-KWS: Effective Keyword Spotting with Multi-head Frame-asynchronous Decoding
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages
Audio Explanation Synthesis with Generative Foundation Models
토론
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