| from emo_gen import EmotionModel, process_func | |
| import librosa | |
| import numpy as np | |
| import torch | |
| from transformers import Wav2Vec2Processor | |
| from config import config | |
| model_name = "./emotional/wav2vec2-large-robust-12-ft-emotion-msp-dim" | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| processor = Wav2Vec2Processor.from_pretrained(model_name) | |
| model = EmotionModel.from_pretrained(model_name).to(device) | |
| def get_emo(path): | |
| wav, sr = librosa.load(path, 16000) | |
| device = config.bert_gen_config.device | |
| return process_func( | |
| np.expand_dims(wav, 0).astype(np.float64), | |
| sr, | |
| model, | |
| processor, | |
| device, | |
| embeddings=True, | |
| ).squeeze(0) | |