Speaker Diarization

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Kurimo, Mikko
dc.contributor.author Macías Ojeda, Antonio
dc.date.accessioned 2014-12-02T11:10:48Z
dc.date.available 2014-12-02T11:10:48Z
dc.date.issued 2014-12-01
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/14569
dc.description.abstract In this thesis we document the development of a system to perform Speaker Diarization, that is, automatically trying to identify who spoke when in a conversation or any other piece of speech with several speakers. The intended usage is to be able to provide this functionality for broadcast news, with data provided by the Finnish broadcasting company YLE under the Next Media programme, financed by TEKES, the Finnish Funding Agency for Technology and Innovation. Another goal is to produce a system compatible with existing Aalto University speech recognition software, in order to open the door to future improvements and research. The produced system, a newly implementation of established methods, with the parameters we determined were the best for our use case, obtains a performance that is very close to current stat-of-the-art systems, while still being compatible with the existing speech recognition software of the Aalto University and having a reasonable speed performance. Further improvements to the system are being made as we speech, opening the door to more research options. en
dc.format.extent 49
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Speaker Diarization en
dc.type G2 Pro gradu, diplomityö en
dc.contributor.school Perustieteiden korkeakoulu fi
dc.subject.keyword speech en
dc.subject.keyword speaker en
dc.subject.keyword recognition en
dc.subject.keyword diarization en
dc.identifier.urn URN:NBN:fi:aalto-201412033122
dc.programme.major Machine Learning and Data Mining fi
dc.programme.mcode SCI3015 fi
dc.type.ontasot Master's thesis en
dc.type.ontasot Diplomityö fi
dc.contributor.supervisor Kurimo, Mikko
dc.programme Master’s Programme in Machine Learning and Data Mining (Macadamia) fi


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