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Automatic dysarthric speech detection exploiting pairwise distance-based convolutional neural networks

Autor: Janbakhshi, P., Kodrasi, I., Bourlard, H.

Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria. In this paper we propose a novel automatic dysarthric speech detection approach based on

Externí odkaz: http://arxiv.org/abs/2011.07545

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Automatic and perceptual discrimination between dysarthria, apraxia of speech, and neurotypical speech

Autor: Kodrasi, I., Pernon, M., Laganaro, M., Bourlard, H.

Automatic techniques in the context of motor speech disorders (MSDs) are typically two-class techniques aiming to discriminate between dysarthria and neurotypical speech or between dysarthria and apraxia of speech (AoS). Further, although such techni

Externí odkaz: http://arxiv.org/abs/2011.07542

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Akademický článek

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Akademický článek

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MLP-based Log Spectral Energy Mapping for Robust Overlapping Speech Recognition

Autor: Bourlard, H., Dines, John, LI, Weifeng

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a3be092c8bc772c5308a05b3f8e6fafb

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Audio-visual processing in meetings: Seven questions and current AMI answers

Publikováno v: 3rd International Workshop on Machine Learning for Multimodal Interaction, MLMI 2006. 1 May 2006 through 4 May 2006, Bethesda, MD., 4299 LNCS, 24-35

The project Augmented Multi-party Interaction (AMI) is concerned with the development of meeting browsers and remote meeting assistants for instrumented meeting rooms - and the required component technologies R&D themes: group dynamics, audio, visual

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e3ec1369c258e5374b2c382646834853
http://resolver.tudelft.nl/uuid:6a07ec27-9cdd-4779-b6e0-832b4257c999

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Automatic Dominance Detection in Meetings using easily obtainable features

Autor: Rienks, R.J., Heylen, Dirk K.J., Bourlard, H., Renals, S.

Publikováno v: Revised Selected Papers of the 2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms MLMI 2005, 76-86
STARTPAGE=76;ENDPAGE=86;TITLE=Revised Selected Papers of the 2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms MLMI 2005

We show that, using a Support Vector Machine classifier, it is possible to determine with a 75% success rate who dominated a particular meeting on the basis of a few basic features. We discuss the corpus we have used, the way we had people judge domi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::553bc9b6727dd690dcf0bf5c635d7131
https://research.utwente.nl/en/publications/b4d659cb-8003-44b7-96e7-eb00b57f78b5

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