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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  • Jan. 29 : CRIM's Journée Techno - 5G
    15/01/2019

    5G: business model transformation, socioeconomic impacts and new technological landscape. Get the tools you need to make the most of these new opportunities!

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  • ICCSP 2019
    21 January 2019 0:00
    Kuala Lumpur, Malaysia
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Recent Publications

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

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  • Checking Sequence Generation for Symbolic Input/Output FSMs by Constraint Solving

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