Automatic audio content analysis
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Comparing images using color coherence vectors
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Automatically extracting highlights for TV Baseball programs
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Content-Based Classification, Search, and Retrieval of Audio
IEEE MultiMedia
On the detection and recognition of television commercials
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Identifying audio clips with RARE
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Inferring similarity between music objects with application to playlist generation
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Extracting story units from long programs for video browsing and navigation
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Discovering nontrivial repeating patterns in music data
IEEE Transactions on Multimedia
A quick search method for audio and video signals based on histogram pruning
IEEE Transactions on Multimedia
ARGOS: automatically extracting repeating objects from multimedia streams
IEEE Transactions on Multimedia
A confidence based recognition system for TV commercial extraction
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Less talk, more rock: automated organization of community-contributed collections of concert videos
Proceedings of the 18th international conference on World wide web
Efficient advertisement discovery for audio podcast content using candidate segmentation
EURASIP Journal on Audio, Speech, and Music Processing
A TV commercial detection system
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
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This paper introduces a novel and very accurate segmentation algorithm. It is very efficient and consumes less than 10% of CPU on a simple desktop PC to segment a stream in real-time. It operates on an audio stream, or on the audio portion of a audio-visual stream. It is very accurate: it accurately detects the positions and durations of objects on an over-the-air broadcast television signal, and songs on both FM and internet radio stations (as checked against labeled ground truth streams). The algorithm does not require any prior information or training. We detail the system design and present results of segmenting broadcast streams.