The construction of speaker-specific acoustic models for automatic speaker recognition is
almost exclusively based on deep neural network-based speaker embeddings. This work …

Initially developed for natural language processing (NLP), Transformer model is now widely
used for speech processing tasks such as speaker recognition, due to its powerful sequence …

The human voice, a dynamic signal, conveys valuable information for speaker identification,
encompassing gender, age, emotions, and language. In the biometrics industry, identifying …

Transformer models are now widely used for speech processing tasks due to their powerful
sequence modeling capabilities. Previous work determined an efficient way to model …

Prior work has shown the utility of acoustic analysis in controlled settings for assessing
chronic obstructive pulmonary disease (COPD)---one of the most common respiratory …

Speaker identification determines an unknown speaker's identity which is a 1: N match
where the speech is compared against multiple templates. Speaker identification is …

Accent recognition (AR) is challenging due to the lack of training data as well as the accents
are entangled with speakers and regional characteristics. This paper aims to improve AR …

Language recognition is the task of predicting the language used in a test speech utterance.
Since 2017, the best performing systems have been based on a deep neural network which …

La tâche de reconnaissance de la langue consiste à prédire la langue utilisée dans un
enregistrement audio contenant de la parole. L'étude d'un tel traitement trouve sa …