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Search on spoken language content inside YouTube videos

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dc.contributor.advisor Bittlingmayer, Adam Mathias
dc.contributor.author Mamikonyan, Tigran
dc.date.accessioned 2022-02-23T07:20:12Z
dc.date.available 2022-02-23T07:20:12Z
dc.date.created 2018
dc.date.issued 2018
dc.identifier.uri https://dspace.aua.am/xmlui/handle/123456789/2133
dc.description Thesis and thesis presentation en_US
dc.description.abstract Every day, millions of people search across YouTube’s billions of videos. The search index is built upon metadata like titles, descriptions and even the content of pages with inbound links. The videos’ image content is also classified and labelled [2]. However, the videos’ audio content itself is not indexed, and thus not used in matching or ranking. Users cannot perform text queries for audio content across videos, nor within a given video. In 2008, YouTube’s parent company Google itself launched a similar project for limited number of political videos [1], but it is not available anymore. This work is an attempt to start solving this issue. The technology makes YouTube videos searchable, building on the recent advances in speech recognition and continued advances in network bandwidth, storage and processing power. en_US
dc.language.iso en_US en_US
dc.publisher American University of Armenia en_US
dc.subject 2018 en_US
dc.subject AUA en_US
dc.subject American University of Armenia (AUA) en_US
dc.subject YouTube en_US
dc.subject Search en_US
dc.subject Speech recognition en_US
dc.subject Closed captions en_US
dc.subject Subtitles en_US
dc.subject Spoken content en_US
dc.title Search on spoken language content inside YouTube videos en_US
dc.type Thesis en_US
dc.academic.department American University of Armenia--College of Science and Engineering


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