The use of artificial intelligence (AI) systems in biomedical and clinical settings can disrupt
the traditional doctor–patient relationship, which is based on trust and transparency in …

Patient-reported outcomes (PROs) and their use in the clinical workflow can improve cancer
survivors' outcomes and quality of life. However, there are several challenges regarding …

Automatic speech recognition (ASR), commonly known as speech-to-text, is the process of
transcribing audio recordings into text, ie, transforming speech into the respective sequence …

The importance and value of real-world data in healthcare cannot be overstated because it
offers a valuable source of insights into patient experiences. Traditional patient-reported …

Problem: Phonetic transcription is crucial in diagnosing speech sound disorders (SSDs) but
is susceptible to transcriber experience and perceptual bias. Current forced alignment (FA) …

This work presents three novel speech recognition architectures evaluated on the Spanish
RTVE2020 dataset, employed as the main evaluation set in the Albayzín S2T Transcription …

Models for keyword spotting in continuous recordings can significantly improve the
experience of navigating vast libraries of audio recordings. In this paper, we describe the …

Recent developments using End-to-End Deep Learning models have been shown to have
near or better performance than state of the art Recurrent Neural Networks (RNNs) on …

In the present society where artificial intelligence (AI) is all over the place, there is a growing
trend in using AI for innovative applications in various academic and industrial fields. This …

In the present society where artificial intelligence (AI) is all over the place, there is a growing
trend in using AI for innovative applications in various academic and industrial fields. This …