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TitleCitationsYearAuthors H-indexModels
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Speech recognition for air traffic control via feature learning and end-to-end training2202113, 3, 5, 18, 10wav2vec2.0 combined with BERT, SincNet,"Deep
Speech 2", Jasper, and Wav2Letter++
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A two-step approach to leverage contextual data: speech recognition in air-traffic communications220224, 7, 4, 5, 27CNN-TDNNF , proposed boosting techniques (G-extension, lattice rescoring, NLP-boosting)
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How Does Pre-trained Wav2Vec2. 0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications020227, 4, 4, 5, 27, -,-,-Wav2Vec2 , XLS-R
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