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--- |
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license: cc-by-sa-4.0 |
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language: |
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- th |
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metrics: |
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- cer |
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- wer |
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library_name: espnet |
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pipeline_tag: automatic-speech-recognition |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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This is the baseline model of Thai-central in [Thai-dialect corpus](https://github.com/SLSCU/thai-dialect-corpus). |
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The training recipe was based on wsj recipe in [espnet](https://github.com/espnet/espnet/). |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This model is a Hybrid CTC/Attention model with pre-trained HuBERT as the encoder. |
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This model was trained on Thai-central to be used as a supervised pre-trained model in order to be used for finetuning to other Thai dialects. (Experiment 2 in the paper). |
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We provide some demo code to do inference with this model on colab [here](https://colab.research.google.com/drive/1stltGdpG9OV-sCl9QgkvEXZV7fGB2Ixe?usp=sharing). (Please note that you cannot inference >4 seconds of audio with free Google colab) |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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For evaluation, the metrics are CER and WER. Before WER evaluation, transcriptions were re-tokenized using newmm tokenizer in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp) |
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```python |
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from pythainlp import word_tokenize |
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tokenized_sentence_list = word_tokenize(<your_sentence>) |
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``` |
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The CER and WER results on the test set are: |
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CER = 2.0 |
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WER = 6.9 |
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## Paper |
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[Thai Dialect Corpus and Transfer-based Curriculum Learning Investigation for Dialect Automatic Speech Recognition](https://www.isca-speech.org/archive/pdfs/interspeech_2023/suwanbandit23_interspeech.pdf) |
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``` |
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@inproceedings{suwanbandit23_interspeech, |
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author={Artit Suwanbandit and Burin Naowarat and Orathai Sangpetch and Ekapol Chuangsuwanich}, |
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title={{Thai Dialect Corpus and Transfer-based Curriculum Learning Investigation for Dialect Automatic Speech Recognition}}, |
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year=2023, |
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booktitle={Proc. INTERSPEECH 2023}, |
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pages={4069--4073}, |
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doi={10.21437/Interspeech.2023-1828} |
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} |
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``` |
