The recent advancements in large language models (LLMs) have revolutionized the field of
natural language processing, progressively broadening their scope to multimodal …

We present CROSSGRAD, a method to use multi-domain training data to learn a classifier
that generalizes to new domains. CROSSGRAD does not need an adaptation phase via …

A field that has directly benefited from the recent advances in deep learning is automatic
speech recognition (ASR). Despite the great achievements of the past decades, however, a …

Speech enhancement and automatic speech recognition (ASR) are most often evaluated in
matched (or multi-condition) settings where the acoustic conditions of the training data …

" This book is an absolute necessity for instructors at all levels, as well as an indispensible
reference for researchers. Introducing NLP, computational linguistics, and speech …

Discriminative learning methods are widely used in natural language processing. These
methods work best when their training and test data are drawn from the same distribution …

In this work we present a new approach to the field of weakly supervised learning in the
video domain. Our method is relevant to sequence learning problems which can be split up …

This paper is an extended abstract which provides a brief preliminary overview of the 2005
Music Information Retrieval Evaluation eXchange (MIREX 2005). The MIREX organizational …

Conditional random fields for sequence labeling offer advantages over both generative
models like HMMs and classifiers applied at each sequence position. Among sequence …

The current need for large multimodal databases to evaluate automatic biometric recognition
systems has motivated the development of the MCYT bimodal database. The main purpose …