Purpose Speech disorders profoundly impact the overall quality of life by impeding social
operations and hindering effective communication. This study addresses the gap in …

The popularity of Deep Neural Networks (DNNs) is growing significantly, and so is the
interest in gaining a better understanding of their functioning. In this work, it is even more …

The automatic prediction of speech intelligibility is a widely known problem in the context of
pathological speech. It has been seen as a growing and viable alternative to perceptual …

Background Speech disorders impact quality of life for patients treated with oral cavity and
oropharynx cancers. However, there is a lack of uniform and applicable methods for …

The automatic prediction of speech intelligibility is a recurrent problem in the context of
pathological speech. Despite recent developments, these systems are normally applied to …

This article reports on vowel clarity metrics based on spectrotemporal modulations of speech
signals. Motivated by previous findings on the relevance of modulation-based metrics for …

The temporal dimension of speech acoustics is rarely taken into account in automatic
models for Speech Intelligibility evaluation, although the rhythmic recurrence of phonemes …

Reliable fundamental frequency (f 0) extraction algorithms are crucial in many fields of
speech research. The current bulk of studies testing the robustness of different algorithms …

Background Perceptual measures such as speech intelligibility are known to be biased,
variant and subjective, to which an automatic approach has been seen as a more reliable …

Perceptual measures, such as intelligibility and speech disorder severity, are widely used in
the clinical assessment of speech disorders in patients treated for oral or oropharyngeal …