Recent work on self-supervised pre-training focus on leveraging large-scale unlabeled
speech data to build robust end-to-end (E2E) acoustic models (AM) that can be later fine …

Personal assistants, automatic speech recognizers and dialogue understanding systems are
becoming more critical in our interconnected digital world. A clear example is air traffic …

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic
controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI) …

Automatic Speech Recognition (ASR), as the assistance of speech communication between
pilots and air-traffic controllers, can significantly reduce the complexity of the task and …

Automatic speech recognition (ASR) allows transcribing the communications between air
traffic controllers (ATCOs) and aircraft pilots. The transcriptions are used later to extract ATC …

In the air traffic management (ATM) environment, air traffic controllers (ATCos) and flight
crews,(FCs) communicate via voice to exchange different types of data such as commands …

Voice communication between air traffic controllers (ATCos) and pilots is critical for ensuring
safe and efficient air traffic control (ATC). This task requires high levels of awareness from …

In air traffic management (ATM), voice communications are critical for ensuring the safe and
efficient operation of aircraft. The pertinent voice communications—air traffic controller …

Air traffic control (ATC) relies on communication via speech between pilot and air-traffic
controller (ATCO). The call-sign, as unique identifier for each flight, is used to address a …

In this work, we propose a method to create domain-sensitive speech recognition models
that utilize textual domain information by conditioning its generation on a given text prompt …