Update README.md
Browse files
README.md
CHANGED
|
@@ -1,3 +1,72 @@
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-4.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
---
|
| 2 |
license: cc-by-nc-4.0
|
| 3 |
+
language:
|
| 4 |
+
- th
|
| 5 |
+
metrics:
|
| 6 |
+
- cer
|
| 7 |
+
- wer
|
| 8 |
+
library_name: espnet
|
| 9 |
+
pipeline_tag: automatic-speech-recognition
|
| 10 |
---
|
| 11 |
+
# Model Card for Model ID
|
| 12 |
+
|
| 13 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 14 |
+
|
| 15 |
+
This is the baseline model of Pattani in [Thai-dialect corpus](https://github.com/SLSCU/thai-dialect-corpus).
|
| 16 |
+
|
| 17 |
+
The training recipe was based on wsj recipe in [espnet](https://github.com/espnet/espnet/).
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
This model is Hybrid CTC/Attention model with pre-trained HuBERT encoder.
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
|
| 29 |
+
## Evaluation
|
| 30 |
+
|
| 31 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 32 |
+
|
| 33 |
+
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)
|
| 34 |
+
|
| 35 |
+
In this reposirity, we also provide the vocabulary for building the newmm tokenizer using this script:
|
| 36 |
+
|
| 37 |
+
```python
|
| 38 |
+
from pythainlp import Tokenizer
|
| 39 |
+
|
| 40 |
+
def get_tokenizer(vocab):
|
| 41 |
+
|
| 42 |
+
custom_vocab = set(vocab)
|
| 43 |
+
custom_tokenizer = Tokenizer(custom_vocab, engine='newmm')
|
| 44 |
+
return custom_tokenizer
|
| 45 |
+
|
| 46 |
+
with open(<vocab_path>,'r',encoding='utf-8') as f:
|
| 47 |
+
vocab = []
|
| 48 |
+
for line in f.readlines():
|
| 49 |
+
vocab.append(line.strip())
|
| 50 |
+
|
| 51 |
+
custom_tokenizer = get_tokenizer(vocab)
|
| 52 |
+
|
| 53 |
+
tokenized_sentence_list = custom_tokenizer.word_tokenize(<your_sentence>)
|
| 54 |
+
```
|
| 55 |
+
|
| 56 |
+
|Micro CER|Macro CER|Survival CER|E-commerce WER|Micro WER|Macro WER|Survival WER|E-commerce WER|
|
| 57 |
+
|---|---|---|---|---|---|---|---|
|
| 58 |
+
|18.17|22.38|31.01|13.75|31.74|37.68|50.54|24.82|
|
| 59 |
+
|
| 60 |
+
## Paper
|
| 61 |
+
|
| 62 |
+
[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)
|
| 63 |
+
```
|
| 64 |
+
@inproceedings{suwanbandit23_interspeech,
|
| 65 |
+
author={Artit Suwanbandit and Burin Naowarat and Orathai Sangpetch and Ekapol Chuangsuwanich},
|
| 66 |
+
title={{Thai Dialect Corpus and Transfer-based Curriculum Learning Investigation for Dialect Automatic Speech Recognition}},
|
| 67 |
+
year=2023,
|
| 68 |
+
booktitle={Proc. INTERSPEECH 2023},
|
| 69 |
+
pages={4069--4073},
|
| 70 |
+
doi={10.21437/Interspeech.2023-1828}
|
| 71 |
+
}
|
| 72 |
+
```
|