LIG at MediaEval 2015 multimodal person discovery in broadcast TV task

Name: LIG at MediaEval 2015 multimodal person discovery in broadcast TV task
Author: Budnik, M., Safadi, B., Besacier, L., Quénot, G., Khodabakhsh, Ali, Demiroğlu, Cenk

İsim	LIG at MediaEval 2015 multimodal person discovery in broadcast TV task
Yazar	Budnik, M., Safadi, B., Besacier, L., Quénot, G., Khodabakhsh, Ali, Demiroğlu, Cenk
Basım Tarihi:	2015
Basım Yeri	- CEUR-WS
Konu	Broadcast TV, Grenoble, Multi-modal, Speech modality, Speech segments
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	1613-0073
Kayıt Numarası	3bd1fd95-313b-49b0-ba16-e255c6b5255e
Lokasyon	Electrical & Electronics Engineering
Tarih	2015
Notlar	ANR
Örnek Metin	In this working notes paper the contribution of the LIG team (partnership between Univ. Grenoble Alpes and Ozyegin University) to the Multimodal Person Discovery in Broadcast TV task in MediaEval 2015 is presented. The task focused on unsupervised learning techniques. Two different approaches were submitted by the team. In the first one, new features for face and speech modalities were tested. In the second one, an alternative way to calculate the distance between face tracks and speech segments is presented. It also had a competitive MAP score and was able to beat the baseline.
Cilt	1436

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LIG at MediaEval 2015 multimodal person discovery in broadcast TV task

Yazar Budnik, M., Safadi, B., Besacier, L., Quénot, G., Khodabakhsh, Ali, Demiroğlu, Cenk

Basım Tarihi 2015

Basım Yeri - CEUR-WS

Konu Broadcast TV, Grenoble, Multi-modal, Speech modality, Speech segments

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 1613-0073

Kayıt Numarası 3bd1fd95-313b-49b0-ba16-e255c6b5255e

Lokasyon Electrical & Electronics Engineering

Tarih 2015

Notlar ANR

Örnek Metin In this working notes paper the contribution of the LIG team (partnership between Univ. Grenoble Alpes and Ozyegin University) to the Multimodal Person Discovery in Broadcast TV task in MediaEval 2015 is presented. The task focused on unsupervised learning techniques. Two different approaches were submitted by the team. In the first one, new features for face and speech modalities were tested. In the second one, an alternative way to calculate the distance between face tracks and speech segments is presented. It also had a competitive MAP score and was able to beat the baseline.

Cilt 1436