Identifying the severity of dysarthria is considered a diagnostic step in monitoring the
patient's progress and a beneficial step in the transcription of dysarthric speech. In this …

Speaker recognition is increasingly used in several everyday applications including smart
speakers, customer care centers and other speech-driven analytics. It is crucial to accurately …

Deep speaker embeddings have been shown to encode a wide variety of attributes relating
to a speaker. The aim of this work is to separate out some of these attributes in the …

The goal of this paper is to learn robust speaker representation for bilingual speaking
scenario. The majority of the world's population speak at least two languages; however …

This paper presents a study on the use of multi-task neural networks (MTNs) for voice-based
soft biometrics recognition, eg, gender, age, and emotion, in social robots. MTNs enable …

This work presents a framework based on feature disentanglement to learn speaker
embeddings that are robust to environmental variations. Our framework utilises an auto …

Due to the scarcity of publicly available diarization data, the model performance can be
improved by training a single model with data from different domains. In this work, we …

This paper proposes a fully explainable approach to speaker verification (SV), a task that
fundamentally relies on individual speaker characteristics. The opaque use of speaker …

Speaker recognition is increasingly used in several everyday applications including smart
speakers, customer care centers and other speech-driven analytics. It is crucial to accurately …

Acoustic environment plays a major role in the performance of a large-scale Automatic
Speech Recognition (ASR) system. It becomes a lot more challenging when substantial …