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Commercial detection based on audio repetition
2008 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Television today is a natural part of many people’s homes. There are technical products that automatically record your favorite shows and programs. The end users ability of choice is a highly valued sales argument in television consumption products. One thing that the user still can not control though is the presence of commercial breaks. Popcatcher is a company that has developed a product that automatically records music from radio stations. What is so special about it, is its ability to distinguish songs from commercial or radio talkers. This is done with help of the fact that popular music is repeated in radio broadcasts. Popcatcher now wants to investigate if the same model can be used to detect commercial in television broadcasts. The goal of this thesis is to build a model and show how well commercial detection could get based on the fact that commercials also are repeated. Different modifications were made to the original algorithm so it eventually formed a commercial scan. One of these modifications was the extended search logistics that determines how the algorithm should react when a potential commercial is found. The model also has a function that somewhat can make up for a failed detection and fill in empty gaps in the detection to some extent. Based on results from a commercial scan made on Swedish TV6, a commercial hit percentage of above 80 percent was achieved when using a seven hours long audio source material. Strong indications show that increasing the source length most likely would improve this percentage further. The commercial scan model presented in this thesis works more like a commercial block detector than an individual commercial detector. One of the draw-backs of the model is the learning time of the system. It has to accumulate and store several hours of input data before giving somewhat fair results. An advantage is the fact that it only analyses audio input in contrary to the often more demanding video analysis other methods use. This thesis shows that commercial detection based on repetition in fact can be done. There is however many improvements left to be made and the work done in this project should be seen as a guidance for further development.

Place, publisher, year, edition, pages
Keyword [en]
Technology, signalbehandling
Keyword [sv]
URN: urn:nbn:se:ltu:diva-44012ISRN: LTU-EX--08/139--SELocal ID: 1d3135b4-cadf-4d07-b01c-bc971bc695ccOAI: diva2:1017286
Subject / course
Student thesis, at least 30 credits
Educational program
Arenaprogrammes (2002-2014)
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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