Inference index info in indentification from trained model

[Tortoise17]

Inference index info in indentification from trained model

[yfchenlucky]

There are many ways. If you don't want to change the code, you can construct wav1, wav2\n wav1 wav3\n and so on, then test pairs and calculate the scores. Or you can simply modify infer_sv.py by fixing the enroll wav and constantly changing the test wav.

[yfchenlucky]

https://github.com/modelscope/3D-Speaker/blob/main/speakerlab/bin/infer_sv.py#L290-L291
You can extract the corresponding embeddings according to the order of enroll and test sets in your wav_path.

[Tortoise17]

@yfchenlucky Great, thank you. If I have to match one wav with files form folder, which has multiple. Could this be possible? to make closest top1-2 matches.?

[Tortoise17]

I guess little change in pipeline will match the possible closest index. Thank you again. If there is still problem, I will request for help.

[Tortoise17]

@yfchenlucky Great help. Really excellent work. Super top architecture models.