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David Doukhan

4 accepted papers

2024

Annotation of Transition-Relevance Places and Interruptions for the Description of Turn-Taking in Conversations in French Media Content

COLING 2024main

Few speech resources describe interruption phenomena, especially for TV and media content. The description of these phenomena may vary across authors: it thus leaves room for improved annotation protocols. We present an annotation of Transition-Relevance Places (TRP) and Floor-Taking event types on…

Cited by 1SourcePDFScholar
2024

InaGVAD : A Challenging French TV and Radio Corpus Annotated for Speech Activity Detection and Speaker Gender Segmentation

COLING 2024main

InaGVAD is an audio corpus collected from 10 French radio and 18 TV channels categorized into 4 groups: generalist radio, music radio, news TV, and generalist TV. It contains 277 1-minute-long annotated recordings aimed at representing the acoustic diversity of French audiovisual programs and was pr…

2021

Speaker Embeddings for Diarization of Broadcast Data In The Allies Challenge

ICASSP 2021accepted

Diarization consists in the segmentation of speech signals and the clustering of homogeneous speaker segments. State-of-the-art systems typically operate upon speaker embeddings, such as i-vectors or neural x-vectors, extracted from mel cepstral coefficients (MFCCs) or spectrograms. The recent SincN…

Cited by 0SourceScholar
2018

An Open-Source Speaker Gender Detection Framework for Monitoring Gender Equality

ICASSP 2018accepted

This paper presents an approach based on acoustic analysis to describe gender equality in French audiovisual streams, through the estimation of male and female speaking time. Gender detection systems based on Gaussian Mixture Models, i-vectors and Convolutional Neural Networks (CNN) were trained usi…

Cited by 0SourceScholar