Automatic Speech Recognition
NeMo
Safetensors
PyTorch
sortformer
speaker-diarization
speaker-recognition
speech
audio
Transformer
FastConformer
Conformer
NEST
NeMo
Eval Results (legacy)
Instructions to use nvidia/diar_sortformer_4spk-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use nvidia/diar_sortformer_4spk-v1 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("nvidia/diar_sortformer_4spk-v1") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
How to use this model to just get audio embedding?
#4
by mohitmayank - opened
Is it possible to use this model for speaker identification and for the same how to use this model to just get audio embedding?
This model does not use speaker representation (speaker embeddings used in speaker verification tasks, e.g. x-vector) so unfortunately you cannot use it for speaker recognition tasks. Try using TitaNet (https://huggingface.co/nvidia/speakerverification_en_titanet_large) in NeMo toolkit which is speaker embedding extractor. You can use speaker embedding on top of Sortformer diarizer's output (filtering out silence etc.).
mohitmayank changed discussion status to closed