Speech Recognition for Uyghur using Speech transformer
Training:
this model using CTC loss and Cross Entropy loss for training.
Download pretrained model and dataset.
unzip results.7z and thuyg20_data.7z to the same folder where python source files located. then run:
python train.py
Recognition:
for recognition download only pretrained model. then run:
python .\tonu.py .\test6.wav
result will be:
Model loaded: results/UFormer_last.pth
Best CER: 4.16%
Trained: 276 epochs
The model has 36,418,306 trainable parameters
Feature has 25,869,058 trainable parameters
Encoder has 4,205,568 trainable parameters
Decoder has 6,343,680 trainable parameters
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Recognizing file .\test6.wav
test6.wav -> u qizlarning resimi chiqip qalsa bilekchila sinchilap qaraytti
This project using
A free Uyghur speech database Released by CSLT@Tsinghua University & Xinjiang University