AUDIO PHRASES FOR AUDIO EVENT RECOGNITION

The bag-of-audio-words approach has been widely used for audio event recognition. In these models, a local fea-ture of an audio signal is matched to a code word according to a learned codebook. The signal is then represented by frequencies of the matched code words on the whole sig-nal. We present in this paper an improved model based on the idea of audio phrases which are sequences of multiple audio words. By using audio phrases, we are able to cap-ture the relationship between the isolated audio words and produce more semantic descriptors. Furthermore, we also propose an efficient approach to learn a compact codebook in a discriminative manner to deal with high-dimensionality of bag-of-audio-phrases representations. Experiments on the Freiburg-106 dataset show that the recognition performance with our proposed bag-of-audio-phrases descriptor outper-forms not only the baselines but also the state-of-the-art results on the dataset. Index Terms — audio phrase, bag-of-words, audio event, recognition, human activity 1