The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …

Deep Neural Networks (DNNs) trained on one dataset (source domain) do not perform well
on another set of data (target domain), which is different but has similar properties as the …

Domain adaptation has become a prominent problem setting in machine learning and
related fields. This review asks the question: How can a classifier learn from a source …

Humans can identify a speaker by listening to their voice, over the telephone, or on any
digital devices. Acquiring this congenital human competency, authentication technologies …

The performance of speech emotion recognition is affected by the differences in data
distributions between train (source domain) and test (target domain) sets used to build and …

Industrial robots (IRs) are promising options for machining large complex structural parts
due to the higher flexibility, larger operating space, and lower cost compared with multi-axis …

Research on speech processing has traditionally considered the task of designing hand-
engineered acoustic features (feature engineering) as a separate distinct problem from the …

Stuttering is a speech disorder during which the flow of speech is interrupted by involuntary
pauses and repetition of sounds. Stuttering identification is an interesting interdisciplinary …

The goal of this work is to train robust speaker recognition models without speaker labels.
Recent works on unsupervised speaker representations are based on contrastive learning …