Automated Audio Captioning (AAC) is the task of generating natural language descriptions
given an audio stream. A typical AAC system requires manually curated training data of …

Sound matching algorithms seek to approximate a target waveform by parametric audio
synthesis. Deep neural networks have achieved promising results in matching sustained …

This study explores the use of a multi-feature Bayesian auditory sound localisation model to
classify non-individual head-related transfer functions (HRTFs). Based on predicted sound …

Deep neural networks (DNNs) for sound recognition learn to categorize a barking sound as
a" dog" and a meowing sound as a" cat" but do not exploit information inherent to the …

Ontologies encompass a formal representation of knowledge through the definition of
concepts or properties of a domain, and the relationships between those concepts. In this …

Recent literature uses language to build foundation models for audio. These Audio-
Language Models (ALMs) are trained on a vast number of audio-text pairs and show …

In this paper, we present a proof-of-concept mechanism for steering latent audio models
through interactive machine learning. Our approach involves mapping the human …

Aging and hearing loss cause communication difficulties, particularly for speech perception
in demanding situations, which have been associated with factors including cognitive …

A vital and comprehensive starting place for understanding the key concepts, this book
explores 177 diverse types and styles of listening named in academic scholarship to date …

This study investigates the information captured by speaker embeddings with relevance to
human speech perception. A Convolutional Neural Network was trained to perform one-shot …