About: Speaker Diarization of Broadcast Streams using Two-stage Clustering based on I-vectors and Cosine Distance Scoring     Goto   Sponge   NotDistinct   Permalink

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Description
  • In this paper we present our system for speaker diarization of broadcast news based on recent advances in the speaker recognition field. In the system, speaker segments determined by the speaker changepoint detector are represented by i-vectors and similarity of segments’ speakers evaluated using cosine distance scoring. Linear discriminant analysis is employed to cope with intra-speaker variability. The experiments were carried out using the COST278 multilingual broadcast news database. We demonstrate improvement of the performance over the baseline system based on the Bayesian Information Criterion (BIC) and highlight significant impact of cepstral mean normalization. Finally, two-stage clustering employing BIC-based clustering to pre-cluster segments in the first stage is examined and showed to yield further performance improvement. The best performing configuration of our system achieved 52.4 % relative improvement of the speaker error rate over the baseline.
  • In this paper we present our system for speaker diarization of broadcast news based on recent advances in the speaker recognition field. In the system, speaker segments determined by the speaker changepoint detector are represented by i-vectors and similarity of segments’ speakers evaluated using cosine distance scoring. Linear discriminant analysis is employed to cope with intra-speaker variability. The experiments were carried out using the COST278 multilingual broadcast news database. We demonstrate improvement of the performance over the baseline system based on the Bayesian Information Criterion (BIC) and highlight significant impact of cepstral mean normalization. Finally, two-stage clustering employing BIC-based clustering to pre-cluster segments in the first stage is examined and showed to yield further performance improvement. The best performing configuration of our system achieved 52.4 % relative improvement of the speaker error rate over the baseline. (en)
Title
  • Speaker Diarization of Broadcast Streams using Two-stage Clustering based on I-vectors and Cosine Distance Scoring
  • Speaker Diarization of Broadcast Streams using Two-stage Clustering based on I-vectors and Cosine Distance Scoring (en)
skos:prefLabel
  • Speaker Diarization of Broadcast Streams using Two-stage Clustering based on I-vectors and Cosine Distance Scoring
  • Speaker Diarization of Broadcast Streams using Two-stage Clustering based on I-vectors and Cosine Distance Scoring (en)
skos:notation
  • RIV/46747885:24220/12:#0002004!RIV13-TA0-24220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(TA01011204)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 170198
http://linked.open...ai/riv/idVysledku
  • RIV/46747885:24220/12:#0002004
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • speaker diarization; broadcast news; clustering; i-vectors (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [BECE5495B368]
http://linked.open...v/mistoKonaniAkce
  • Tokyo, Japonsko
http://linked.open...i/riv/mistoVydani
  • Japonsko
http://linked.open...i/riv/nazevZdroje
  • Proc. of International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2012
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Pražák, Jan
  • Silovský, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000312381404066
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-1-4673-0046-9
http://localhost/t...ganizacniJednotka
  • 24220
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