Keywords:
- Air traffic control
- air traffic control communications
- articulatory features
- Automatic Speech Recognition
- BNF
- Cross-lingual automatic speech recognition (ASR)
- Deep neural network
- deep neural networks
- domain-adversarial neural network
- Language targets
- Lattice-Free MMI
- LID
- multi-stream learning
- self-supervised pre-training
- transfer learning
- wav2vec 2.0
Publications of Qingran Zhan
2023
| How Does Pre-trained Wav2Vec 2.0 Perform on Domain-Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications, , , , , , , , and , in: 2023 IEEE Spoken Language Technology Workshop (SLT), IEEE, 2023 |
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2021
| Broadcast Media Content Categorization Using Low-Resolution Concepts, , , , and , Idiap-RR-06-2021 |
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| Cross-lingual Automatic Speech Recognition Exploiting Articulatory Features, , , , and , Idiap-RR-05-2021 |
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| Domain-Adversarial Based Model with Phonological Knowledge for Cross-Lingual Speech Recognition, , , , , and , in: Electronics, 10(24):1-15, 2021 |
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2020
| Automatic Speech Recognition Benchmark for Air-Traffic Communications, , , , and , in: Proc. Interspeech 2020, pages 2297-2301, 2020 |
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| Idiap & UAM participation at GermEval 2020: Classification and Regression of Cognitive and Motivational Style from Text, , , , and , in: Proceedings of the GermEval 2020 Shared Task on the Classification and Regression of Cognitive and Motivational style from Text, 2020 |
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| Idiap Submission to Swiss-German Language Detection Shared Task, , , , and , Idiap-RR-11-2020 |
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| Idiap Submission to Swiss-German Language Detection Shared Task, , , , and , in: Proceedings of the 5th Swiss Text Analytics Conference (SwissText) & 16th Conference on Natural Language Processing (KONVENS), CEUR Workshop Proceedings, 2020 |
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2019
| Cross-lingual Automatic Speech Recognition Exploiting Articulatory Features, , , , , and , in: Proceedings of APSIPA ASC 2019, 2019 |
| SPOKEN LANGUAGE IDENTIFICATION USING LANGUAGE BOTTLENECK FEATURES, , , , , and , Idiap-RR-08-2019 |
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| Spoken language identification using language bottleneck features, , , , , and , in: Proceedings of TSD, 2019 |
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