Automated speech recognition (ASR) systems, which use sophisticated machine-learning
algorithms to convert spoken language to text, have become increasingly widespread …

Practice and recent evidence show that state-of-the-art (SotA) automatic speech recognition
(ASR) systems do not perform equally well for all speaker groups. Many factors can cause …

Automatic speech recognition (ASR) systems promise to deliver objective interpretation of
human speech. Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs …

This study investigates Whisper's automatic speech recognition (ASR) system performance
across diverse native and non-native English accents. Results reveal superior recognition in …

Natural language processing (NLP) tools are increasingly used to quantify semantic
anomalies in schizophrenia. Automatic speech recognition (ASR) technology, if robust …

Despite years of speech recognition research, little is known about which words tend to be
misrecognized and why. Previous work has shown that errors increase for infrequent words …

Students may encounter problems concentrating during a lecture due to various reasons,
which can be related to the educator's accent or the student's auditory difficulties. This may …

The use of automatic speech recognition (ASR) has been increasing to promote inclusion
and accessibility. Nonetheless, prior work on ASR finds performance gaps conditioned by …

This paper analyzes the gender representation in four major corpora of French broadcast.
These corpora being widely used within the speech processing community, they are a …

In this paper, we describe the outcomes of the challenge organized and run by Airbus and
partners in 2018. The challenge consisted of two tasks applied to Air Traffic Control (ATC) …