如何提取音频特征 #49
Description
我刚试了一下实例代码
# fairseq 使用
import torch
import torch.nn.functional as F
import soundfile as sf
from fairseq import checkpoint_utils
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model_path=""
wav_path=""
def postprocess(feats, normalize=False):
if feats.dim() == 2:
feats = feats.mean(-1)
assert feats.dim() == 1, feats.dim()
if normalize:
with torch.no_grad():
feats = F.layer_norm(feats, feats.shape)
return feats
print("loading model(s) from {}".format(model_path))
models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
[model_path],
suffix="",
)
print("loaded model(s) from {}".format(model_path))
print(f"normalize: {saved_cfg.task.normalize}")
model = models[0]
model = model.to(device)
model = model.half()
model.eval()
wav, sr = sf.read(wav_path)
feat = torch.from_numpy(wav).float()
feat = postprocess(feat, normalize=saved_cfg.task.normalize)
feats = feat.view(1, -1)
padding_mask = (
torch.BoolTensor(feats.shape).fill_(False)
)
inputs = {
"source": feats.half().to(device),
"padding_mask": padding_mask.to(device),
}
with torch.no_grad():
logits = model.extract_features(**inputs)
print(logits)返回是这样子的
不知道是不是把这块的数据提取出来做reshape就可以了