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--- |
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license: apache-2.0 |
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language: |
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- th |
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- en |
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base_model: |
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- openai/whisper-large-v3 |
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pipeline_tag: automatic-speech-recognition |
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library_name: transformers |
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metrics: |
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- wer |
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--- |
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# Pathumma Whisper Large V3 (TH) |
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More information needed |
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## Model Description |
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More information needed |
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## Quickstart |
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More information needed |
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## Evaluation Performance |
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| Model | WER (CV18) | WER (Gowejee) | WER (LOTUS-TRD) | WER (Thai Dialect) | WER (Elderly) | WER (Gigaspeech2) | WER (Fleurs) | WER (Distant Meeting) | WER (Podcast) | |
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|:----------------------------------------|:----------------------:|:-------------------------:|:----------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|:--------------------------:| |
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| whisper-large-v3 | 18.75 | 46.59 | 48.14 | 57.82 | 12.27 | 33.26 | 24.08 | 72.57 | 41.24 | |
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| airesearch-wav2vec2-large-xlsr-53-th | 8.49 | 17.28 | 63.01 | 48.53 | 11.29 | 52.72 | 37.32 | 85.11 | 65.12 | |
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| thonburian-whisper-th-large-v3-combined | 7.62 | 22.06 | 41.95 | 26.53 | 1.63 | 25.22 | 13.90 | 64.68 | 32.42 | |
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| monsoon-whisper-medium-gigaspeech2 | 11.66 | 20.50 | 41.04 | 42.06 | 7.57 | 21.40 | 21.54 | 51.65 | 38.89 | |
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| pathumma-whisper-th-large-v3 | 8.68 | 9.84 | 15.47 | 19.85 | 1.53 | 21.66 | 15.65 | 51.56 | 36.47 | |
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## Limitations |
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More information needed |
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## Acknowledgements |
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We extend our appreciation to the research teams engaged in the creation of the open speech model, including AIResearch, BiodatLab, Looloo Technology, SCB 10X, and OpenAI. We would like to express our gratitude to Dr. Titipat Achakulwisut of BiodatLab for the evaluation pipeline. We express our gratitude to ThaiSC, or NSTDA Supercomputer Centre, for supplying the LANTA used for model training, fine-tuning, and evaluation. |
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## Pathumma Audio Team |
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*Pattara Tipkasorn*, Wayupuk Sommuang, Oatsada Chatthong, *Kwanchiva Thangthai* |
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## Citation |
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More information needed |
