mamyrbek/AudioLanguageIdentification

import torchaudio
import torch
import time
from speechbrain.inference import EncoderClassifier

device = "cuda:5" if torch.cuda.is_available() else "cpu"
run_opts = {"device": device}
language_id = EncoderClassifier.from_hparams(source="./checkpoint", # change the cp folder path
                                             savedir="tmp",
                                             run_opts=run_opts)
# language_id.to('cuda:5')
# Download Thai language sample from Omniglot and convert to suitable form

signal = language_id.load_audio('test.wav')
prediction =  language_id.classify_batch(signal)
print(f"prediction: {prediction})