Speaker-Verification
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Verifying the identity of a person from characteristics of the voice independent from language via NVIDIA NeMo models (ECAPA-TDNN, SpeakerNet, TitaNet-L).
Speaker Verification
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:
Download Models - Save and Load Speaker Vectors
You can download Nemo models and speaker vectors for SpeakerNet, TitaNet-L, ECAPA-TDNN from files/
.
Prediction
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
Inference Benchmark
- Torch Model
- Onnx Model Run the script below to compare the inference time of SpeakerNet model.
speaker_verification_with_torch_and_onnx.ipynb