This survey provides an overview of the evolution of visually grounded models of spoken
language over the last 20 years. Such models are inspired by the observation that when …

Existing speech to speech translation systems heavily rely on the text of target language:
they usually translate source language either to target text and then synthesize target …

Transformers have made significant strides across various artificial intelligence domains,
including natural language processing, computer vision, and audio processing. This …

Safety helmets play a vital role in protecting workers' heads. In order to improve the accuracy
of the detection model in complex environments, such as complex backgrounds and …

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model
training problematic for most existing languages, including languages that do not even have …

The idea of combining multiple languages' recordings to train a single automatic speech
recognition (ASR) model brings the promise of the emergence of universal speech …

Text-based technologies, such as text translation from one language to another, and image
captioning, are gaining popularity. However, approximately half of the world's languages are …

Many computational models of speech recognition assume that the set of target words is
already given. This implies that these models learn to recognise speech in a biologically …

Keyword localisation is the task of finding where in a speech utterance a given query
keyword occurs. We investigate to what extent keyword localisation is possible using a …

We improve low-resource ASR by integrating the ideas of multilingual training and self-
supervised learning. Concretely, we leverage an International Phonetic Alphabet (IPA) …