Speaker verification is verifying the identity of a person from characteristics of the voice independent from language via NVIDIA NeMo.
This reporisitory presents three NeMo speaker verification models:
You can download Nemo models and speaker vectors for SpeakerNet, TitaNet-L, ECAPA-TDNN from files/.
The cosine similarity metric was used for prediction.
from sklearn.metrics.pairwise import cosine_similarity
sims = cosine_similarity([vector[0]], speakers_vectors)[0]To predict most similar speaker in test_voices/ refered to ref_voices run the following command:
python speaker_verification.py- Torch Model
- Onnx Model Run the script below to compare the inference time of SpeakerNet model.
speaker_verification_with_torch_and_onnx.ipynb