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Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations
In the context of telephone conversations, we can break down the audio information into acoustic and linguistic by using the speech signal and its transcription.
On the use of Self-supervised Pre-trained Acoustic and Linguistic Features for Continuous Speech Emotion Recognition
Pre-training for feature extraction is an increasingly studied approach to get better continuous representations of audio and text content.
Pr\'ediction continue de la satisfaction et de la frustration dans des conversations de centre d'appels (AlloSat : A New Call Center French Corpus for Affect Analysis)
AlloSat regroupe 303 conversations pour un total d{'}environ 37 heures d{'}audio, toutes enregistr{\'e}es dans des environnements r{\'e}els, collect{\'e}es par Allo-Media (une soci{\'e}t{\'e} sp{\'e}cialis{\'e}e dans l{'}analyse automatique d{'}appels).
AlloSat: A New Call Center French Corpus for Satisfaction and Frustration Analysis
We present a new corpus, named AlloSat, composed of real-life call center conversations in French that is continuously annotated in frustration and satisfaction.
