Audio analytics

Our team encompasses a set of skills dedicated to the extraction of information from an audio signal. 

An audio recording often contains more than one speaker. The process of diarisation partitions the audio signal into speaker segments, even when speaker are not known beforehand. Keyword detection consists in identifying the presence of certain words within audio recordings, whereas topic detection determines if a given subject has been discussed during a conversation. When the task is to accurately determine the position of each word or phoneme of a recording, we  speak of text/audio synchronization. We have also developed algorithms aimed at detecting a person’s emotions from an audio recording. It then becomes possible, in an automated system, to modify the system’s behavior according to the user’s reaction in order to adequately satisfy his interlocutor.

Related technologies: keyword detection, audio content indexing, emotion detection 

 

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Recent news

  • Blogue du CRIM - Manipuler les variables catégoriques dans un jeu de données
    12/07/2018

    Dans cet article, Farooq Sanni et Martin Sotir nous présentent différentes méthodes et astuces pour gérer les variables catégoriques.

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Upcoming event

  • QRS - SSCPS - IA 2018
    20 July 2018 0:00
    Lisbonne, Portugal
    Le CRIM présentera trois articles scientifiques au QRS 2018.
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Recent Publications

  • Towards Automatic Feature Extraction for Activity Recognition from Wearable Sensors: A Deep Learning Approach

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  • État des lieux des technologies web

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