Soundtrack classification by transient events

We present a method for video classification based on information in the soundtrack. Unlike previous approaches which describe the audio via statistics of mel-frequency cepstral coefficient (MFCC) features calculated on uniformly-spaced frames, we investigate an approach to focusing our representati...

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Bibliographic Details
Published in2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 473 - 476
Main Authors Cotton, Courtenay V., Ellis, Daniel P. W., Loui, Alexander C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Acoustic signal processing
Feature extraction
Gain control
Histograms
Mel frequency cepstral coefficient
Multimedia databases
Semantics
Time frequency analysis
Transient analysis
Video indexing
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Summary:We present a method for video classification based on information in the soundtrack. Unlike previous approaches which describe the audio via statistics of mel-frequency cepstral coefficient (MFCC) features calculated on uniformly-spaced frames, we investigate an approach to focusing our representation on audio transients corresponding to sound-track events. These event-related features can reflect the "foreground" of the soundtrack and capture its short-term temporal structure better than conventional frame-based statistics. We evaluate our method on a test set of 1873 YouTube videos labeled with 25 semantic concepts. Retrieval results based on transient features alone are comparable to an MFCC-based system, and fusing the two representations achieves a relative improvement of 7.5% in mean average precision (MAP).
ISBN:9781457705380
1457705389
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2011.5946443