nlpatl.models.embeddings.nemo

class nlpatl.models.embeddings.nemo.Nemo(model_name_or_path='titanet_large', batch_size=16, target_sr=16000, device='cuda', name='nemo')[source]

Bases: nlpatl.models.embeddings.embeddings.Embeddings

A wrapper of nemo class.

Parameters

model_name_or_path (str) – nemo model name. Verifeid. titanet_large, speakerverification_speakernet and ecapa_tdnn. Refer to https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/speaker_recognition/intro.html
batch_size (int) – Batch size of data processing. Default is 16
target_sr (int) – Sample rate. Audio will be resample to this value.
device (str) – Device for processing data
name (str) – Name of this embeddings

>>> import nlpatl.models.embeddings as nme
>>> model = nme.Nemo()

convert(x)[source]

Parameters: x (np.ndarray) – Raw features
Returns: Vectors of features
Return type: np.ndarray