Word recognition in a model of visually grounded speech: An analysis using techniques inspired by human speech processing research

A Visually Grounded Speech model is a neural model which is trained to embed image caption pairs closely together in a common embedding space. As a result, such a model can retrieve semantically related images given a speech caption and vice versa. The purpose of this research is to investigate whether and how a Visually Grounded Speech model...

Bringing digital scribes into orthopedic consultations: Towards AI-assisted clinical documentation

Clinical documentation takes up 40% of clinicians’ time. To ease the administrative burden of clinicians, digital scribes offer the potential to automate clinical note taking. Digital scribes are intelligent documentation softwares that combine automated speech recognition (ASR) and natural language processing (NLP). Digital scribes transcribe...

Automatic Speech Recognition for Air Traffic Control Using Open Data

Air Traffic Control (ATC) is tasked with ensuring safe separation between aircraft in a given Controlled Traffic Region (CTR). To achieve this an Air Traffic Controller (ATCo) verbally gives clearances using over the air communication. These clearances are kept track of by the ATCo using so-called ‘flight-strips’, which in modern systems are...

Applying Large-Scale Weakly Supervised Automatic Speech Recognition to Air Traffic Control

The application of automatic speech recognition in the air traffic control domain has been researched extensively. However, its primary application remains in the training and simulation of air traffic controllers. This is due to the insufficient performance of automatic speech recognition in specific environments, such as air traffic control,...