With the COVID-19 pandemic, the wearing of face masks covering mouth and nose has
become ubiquitous all around the world. This study investigates the impact of typical face …

We compare two alternative speech intelligibility prediction algorithms: time-frequency
glimpse proportion (GP) and spectro-temporal glimpsing index (STGI). Both algorithms …

Spectro-temporal modulations are believed to mediate the analysis of speech sounds in the
human primary auditory cortex. Inspired by humans' robustness in comprehending speech …

Temporal contrasts in speech are perceived relative to the speech rate of the surrounding
context. That is, following a fast context sentence, listeners interpret a given target sound as …

We propose a monaural intrusive speech intelligibility prediction (SIP) algorithm called STGI
based on detecting glimpses in short-time segments in a spectro-temporal modulation …

Room acoustics models are often used in auditory research. The simplest implementations
of these models ignore air absorption, and this lack can affect the room response, especially …

This study investigated how acoustic and lexical word-level factors and listener-level factors
of auditory thresholds and cognitive-linguistic processing contribute to the microstructure of …

Many existing speech intelligibility prediction (SIP) algorithms can only account for acoustic
factors affecting speech intelligibility and cannot predict intelligibility across corpora with …

3D audio spatializers for Virtual Reality (VR) can use the acoustic properties of the surfaces
of a visualised game space to calculate a matching reverb. However, this approach could …

Recent advances in deep learning have improved the capabilities of data-driven speech
intelligibility prediction (SIP) algorithms. Nevertheless, the scarcity of speech intelligibility …