Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging

Overview of attention for article published in IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), May 2017

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In the top 25% of all research outputs scored by Altmetric
Good Attention Score compared to outputs of the same age (79th percentile)
Good Attention Score compared to outputs of the same age and source (79th percentile)

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RT @markplumbley: Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging https://t.co/sY2ODFIYfO #OA @yong_ustc…

Environmental audio tagging of acoustical events using asymmetric deep denoising auto-encoder (DNN) with 0.15 equal error rate on DCASE 2016 https://t.co/mHdeK2bKeY

Unsupervised Feature Learning Based on Deep Models for Environmental Audio Tagging https://t.co/sY2ODFIYfO #OA @yong_ustc @drphilipjackson

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