Create README.md

README.md

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+---
+license: cc-by-sa-4.0
+language:
+- th
+metrics:
+- cer
+- wer
+library_name: espnet
+pipeline_tag: automatic-speech-recognition
+---
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This is the baseline model of Thai-central in [Thai-dialect corpus](https://github.com/SLSCU/thai-dialect-corpus).
+
+The training recipe was based on wsj recipe in [espnet](https://github.com/espnet/espnet/).
+
+
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This model is Hybrid CTC/Attention model with pre-trained HuBERT as the encoder.
+
+This model trained on Thai-central for being the supervised pre-trained model in transfer-based curriculum learning experiment.
+
+you can demo on colab with [this link](https://colab.research.google.com/drive/1stltGdpG9OV-sCl9QgkvEXZV7fGB2Ixe?usp=sharing). (Free google colab cannot inferences > 3 seconds of speech.)
+
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+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)
+
+In this reposirity, we also provide the vocabulary for building the newmm tokenizer using this script:
+
+```python
+from pythainlp import word_tokenize
+
+tokenized_sentence_list = word_tokenize(<your_sentence>)
+```
+
+CER = 2.0
+WER = 6.9
+
+## Paper
+
+[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)
+```
+@inproceedings{suwanbandit23_interspeech,
+  author={Artit Suwanbandit and Burin Naowarat and Orathai Sangpetch and Ekapol Chuangsuwanich},
+  title={{Thai Dialect Corpus and Transfer-based Curriculum Learning Investigation for Dialect Automatic Speech Recognition}},
+  year=2023,
+  booktitle={Proc. INTERSPEECH 2023},
+  pages={4069--4073},
+  doi={10.21437/Interspeech.2023-1828}
+}
+```