whisper-small-atc

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Whisper Small ATC - ATCText

This model is a fine-tuned version of openai/whisper-small on the ATC dataset. It achieves the following results on the evaluation set:

• Loss: 0.2486
• Wer: 10.6129

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 4000

Training results

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2
• Datasets 2.18.0
• Tokenizers 0.15.2

Additional Information

Licensing Information

The licensing status of the dataset hinges on the legal status of the UWB-ATCC corpus creators.

They used Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) licensing.

Citation Information

Contributors who prepared, processed, normalized and uploaded the dataset in HuggingFace:

@article{zuluaga2022how, title={How Does Pre-trained Wav2Vec2. 0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications}, author={Zuluaga-Gomez, Juan and Prasad, Amrutha and Nigmatulina, Iuliia and Sarfjoo, Saeed and others}, journal={IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar}, year={2022} }

@article{zuluaga2022bertraffic, title={BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications}, author={Zuluaga-Gomez, Juan and Sarfjoo, Seyyed Saeed and Prasad, Amrutha and others}, journal={IEEE Spoken Language Technology Workshop (SLT), Doha, Qatar}, year={2022} }

@article{zuluaga2022atco2, title={ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications}, author={Zuluaga-Gomez, Juan and Vesel{`y}, Karel and Sz{"o}ke, Igor and Motlicek, Petr and others}, journal={arXiv preprint arXiv:2211.04054}, year={2022} }

Authors of the dataset:

@article{vsmidl2019air, title={Air traffic control communication (ATCC) speech corpora and their use for ASR and TTS development}, author={{\v{S}}m{'\i}dl, Lubo{\v{s}} and {\v{S}}vec, Jan and Tihelka, Daniel and Matou{\v{s}}ek, Jind{\v{r}}ich and Romportl, Jan and Ircing, Pavel}, journal={Language Resources and Evaluation}, volume={53}, number={3}, pages={449--464}, year={2019}, publisher={Springer} }