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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.00614 |
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| _version_ | 1866908493614678016 |
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| author | Nakilcioglu, Emin Cagatay Reimann, Maximilian John, Ole |
| author_facet | Nakilcioglu, Emin Cagatay Reimann, Maximilian John, Ole |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_00614 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Adaptation and Optimization of Automatic Speech Recognition (ASR) for the Maritime Domain in the Field of VHF Communication Nakilcioglu, Emin Cagatay Reimann, Maximilian John, Ole Sound Artificial Intelligence Human-Computer Interaction Machine Learning Audio and Speech Processing 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. |
| title | Adaptation and Optimization of Automatic Speech Recognition (ASR) for the Maritime Domain in the Field of VHF Communication |
| topic | Sound Artificial Intelligence Human-Computer Interaction Machine Learning Audio and Speech Processing |
| url | https://arxiv.org/abs/2306.00614 |