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from emo_gen import EmotionModel, process_func
import librosa
import numpy as np
import torch
from transformers import Wav2Vec2Processor
def get_emo(path):
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)
wav, sr = librosa.load(path, 16000)
# device = config.bert_gen_config.device
return process_func(
np.expand_dims(wav, 0).astype(float),
sr,
model,
processor,
device,
embeddings=True,
).squeeze(0)
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