Deep Neural Network Bottleneck Feature for Acoustic Scene Classification
نویسندگان
چکیده
Bottleneck features have been shown to be effective in improving the accuracy of speaker recognition, language identification and automatic speech recognition. However, few works have focused on bottleneck features for acoustic scene classification. This report proposes a novel acoustic scene feature extraction using bottleneck features derived from a Deep Neural Network (DNN). On the official development set with our settings, a feature set that includes bottleneck features and Perceptual Linear Prediction (PLP) feature shows a best accuracy rate.
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