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Found 15 papers, 1 papers with code
Overlaps and Gender Analysis in the Context of Broadcast Media
Our main goal is to study the interactions between speakers according to their gender and role in broadcast media.
A Semi-Automatic Approach to Create Large Gender- and Age-Balanced Speaker Corpora: Usefulness of Speaker Diarization & Identification.
It shows the automatic processing compare to up-to-date process, and that the output provides high quality speech for most of the selected excerpts.
Unsupervised Multiple Domain Translation through Controlled Disentanglement in Variational Autoencoder
One of this latent variables is imposed to depend exclusively on the domain, while the other one must depend on the rest of the variability factors of the data.
An Explainable Proxy Model for Multiabel Audio Segmentation
Audio signal segmentation is a key task for automatic audio indexing.
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.
Joint speech and overlap detection: a benchmark over multiple audio setup and speech domains
Voice activity and overlapped speech detection (respectively VAD and OSD) are key pre-processing tasks for speaker diarization.
Evaluation of Speaker Anonymization on Emotional Speech
This paper studies the impact of the speaker anonymization baseline system of the VPC on emotional information present in speech utterances.
Training speech emotion classifier without categorical annotations
There are two paradigms of emotion representation, categorical labeling and dimensional description in continuous space.
Overlapped speech and gender detection with WavLM pre-trained features
This article focuses on overlapped speech and gender detection in order to study interactions between women and men in French audiovisual media (Gender Equality Monitoring project).
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).
Towards Interactive Annotation for Hesitation in Conversational Speech
Furthermore, regression models were trained in order to allow automatic prediction of hesitation for speech chunks that do not have a manual annotation.
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.
Corpus of Children Voices for Mid-level Markers and Affect Bursts Analysis
This article presents a corpus featuring children playing games in interaction with the humanoid robot Nao: children have to express emotions in the course of a storytelling by the robot.
