Adaptation and Optimization of Automatic Speech Recognition (ASR) for the Maritime Domain in the Field of VHF Communication
This work addresses the challenge of converting VHF radio signals into text for the maritime domain, but it appears incremental as it adapts existing ASR methods to a specific application.
The paper tackled the problem of transcribing VHF radio signals in maritime communication by developing a multilingual automatic speech recognizer (ASR) called marFM, which uses deep learning and audio processing techniques, and evaluated its transcription performance on maritime radio data.
This paper introduces a multilingual automatic speech recognizer (ASR) for maritime radio communi-cation that automatically converts received VHF radio signals into text. The challenges of maritime radio communication are described at first, and the deep learning architecture of marFM consisting of audio processing techniques and machine learning algorithms is presented. Subsequently, maritime radio data of interest is analyzed and then used to evaluate the transcription performance of our ASR model for various maritime radio data.