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@@ -12,7 +12,6 @@ metrics:
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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
@@ -53,7 +52,7 @@ WER calculated with newmm tokenizer for Thai word segmentation.
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  **Note:** Other models not target fine-tuned on dialect datasets may be less representative of dialect performance.
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- ## Limitations
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  More information needed
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  ## Acknowledgements
@@ -63,4 +62,10 @@ We extend our appreciation to the research teams engaged in the creation of the
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  *Pattara Tipkasorn*, Wayupuk Sommuang, Oatsada Chatthong, *Kwanchiva Thangthai*
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  ## Citation
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- More information needed
 
 
 
 
 
 
 
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  ---
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  # Pathumma Whisper Large V3 (TH)
 
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  ## Model Description
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  More information needed
 
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  **Note:** Other models not target fine-tuned on dialect datasets may be less representative of dialect performance.
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+ ## Limitations and Future Work
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  More information needed
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  ## Acknowledgements
 
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  *Pattara Tipkasorn*, Wayupuk Sommuang, Oatsada Chatthong, *Kwanchiva Thangthai*
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  ## Citation
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+ @misc{tipkasorn2024PathummaWhisper,
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+ title = { {Pathumma Whisper Large V3 (TH)} },
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+ author = { Pattara Tipkasorn and Wayupuk Sommuang and Oatsada Chatthong and Kwanchiva Thangthai },
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+ url = { https://huggingface.co/nectec/Pathumma-whisper-th-large-v3 },
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+ publisher = { Hugging Face },
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+ year = { 2024 },
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+ }