Deep learning approaches have achieved great success in the field of Natural Language
Processing (NLP). However, directly training deep neural models often suffer from overfitting …

Intent classification, to identify the speaker's intention, and slot filling, to label each token
with a semantic type, are critical tasks in natural language understanding. Traditionally the …

Patient care, diagnosis, and treatment could all be revolutionized by the use of artificial
intelligence (AI) in healthcare. This essay investigates the broad implications of AI in …

Spoken Language Understanding (SLU), a core component of the task-oriented dialogue
system, expects a shorter inference latency due to the impatience of humans. Non …

A new era of medical innovations has begun as a result of the quick adoption of artificial
intelligence (AI) in healthcare, which is changing many aspects of patient care and medical …

Conversational emotion recognition (CER) has attracted increasing interests in the natural
language processing (NLP) community. Different from the vanilla emotion recognition …

This article discusses the role of machine learning in contact tracing for public health,
particularly in controlling the spread of infectious diseases like COVID-19. The traditional …

Joint intent detection and slot filling is a key research topic in natural language
understanding (NLU). Existing joint intent and slot filling systems analyze and compute …

In the field of healthcare, artificial intelligence (AI) has emerged as a paradigm-shifting force,
upending established procedures and promising unmatched improvements. This in-depth …