Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards robust features for classifying audio in the CueVideo system
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
A robust audio classification and segmentation method
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Real-time discrimination of broadcast speech/music
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
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Audio classification has been investigated for several years. It is one of the key components in audio and video applications. In prior work, the accuracy under complicated condition is not satisfactory enough and the results highly depend on the dataset. In this paper, we present a novel audio classification method based on maximum entropy model. By applying this method on some widely used features, different feature combinations are considered during model training and a better performance can be achieved. When evaluated it in TREC 2002 Video Track's speech/music feature extraction task, this method works well for both speech and music among participated systems.