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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  • Découvrez le CRIM
    13/02/2020

    Acteur clé en TI au Québec ; un lien entre les mondes universitaire et industriel, qui développe, adapte et rend accessibles les technologies et les connaissances, pour répondre aux besoins des organisations.

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Upcoming event

  • Seminar R&D : Automated speech-to-text transcription of Indigenous Languages
    28 February 2020 11:00
    CRIM (405, avenue Ogilvy, bureau 101, Montréal)
    A conference of Gilles Boulianne and Vishwa Gupta, Senior Researchers in Automatic Speech Processing, CRIM.
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Recent Publications

  • Validating BGP Update Using Blockchain-Based Infrastructure

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  • Efficient Inference of Optimal Decision Trees

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