Learning a set of tasks in sequence remains a challenge for artificial neural networks, which,
in such scenarios, tend to suffer from Catastrophic Forgetting (CF). The same applies to End …

The ability to learn new concepts sequentially is a major weakness for modern neural
networks, which hinders their use in non-stationary environments. Their propensity to fit the …

Intrusion detection is a form of anomalous activity detection in communication network traffic.
Continual learning (CL) approaches to the intrusion detection task accumulate old …

Keyword Spotting (KWS) models on embedded devices should adapt fast to new user-
defined words without forgetting previous ones. Embedded devices have limited storage …

Automatic speech recognition research focuses on training and evaluating on static
datasets. Yet, as speech models are increasingly deployed on personal devices, such …

Recently, neural networks have shown impressive progress across diverse fields, with
speech processing being no exception. However, recent breakthroughs in this area require …

While external language models (LMs) are often incorporated into the decoding stage of
automated speech recognition systems, these models usually operate with limited context …

Emotions provide critical information regarding a person's health and well-being. Therefore,
the ability to track emotion and patterns in emotion over time could provide new …

Emotion conveys abundant information that can improve the user experience of various
automated systems, in addition to communicating information important for managing …

Continual learning has emerged as an increasingly important challenge across various
tasks, including Spoken Language Understanding (SLU). In SLU, its objective is to …