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The Intelligent Voice System for the IberSPEECH-RTVE 2018 Speaker Diarization Challenge

Abbas Khosravani Cornelius Glackin Nazim Dugan Gérard Chollet 1, 2 Nigel Cannings 
1 MM - Multimédia
LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : This paper describes the Intelligent Voice (IV) speaker diarization system for IberSPEECH-RTVE 2018 speaker diarization challenge. We developed a new speaker diarization built on the success of deep neural network based speaker embeddings in speaker verification systems. In contrary to acoustic features such as MFCCs, deep neural network embeddings are much better at discerning speaker identities especially for speech acquired without constraint on recording equipment and environment. We perform spectral clustering on our proposed CNNLSTM-based speaker embeddings to find homogeneous segments and generate speaker log likelihood for each frame. A HMM is then used to refine the speaker posterior probabilities through limiting the probability of switching between speakers when changing frames. We present results obtained on the development set (dev2) as well as the evaluation set …
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Submitted on : Friday, September 13, 2019 - 5:34:34 PM
Last modification on : Wednesday, November 3, 2021 - 6:18:51 AM


  • HAL Id : hal-02287998, version 1


Abbas Khosravani, Cornelius Glackin, Nazim Dugan, Gérard Chollet, Nigel Cannings. The Intelligent Voice System for the IberSPEECH-RTVE 2018 Speaker Diarization Challenge. IberSPEECH, Nov 2018, Barcelone, Spain. pp.231-235. ⟨hal-02287998⟩



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