Can Nguyen
Can Nguyen

Reputation: 11

Which feature, algorithm is good for Speaker Verification

I have a task with speaker verification.

My task is calculate the similarity between two audio speech voice, then compare with a threshold. Ex: similarity score between two audio is 70%, threshold is 50%. Hence the speaker is the same person.

The speech is text-independent, it's can be any conversation.

I have experiment in using MFCC, GMM for speaker recognition task, but this task is difference, just compare two audio feature to have the similarity score. I don't know which feature is good for speaker verification and which algorithm can help me to calculate similarity score between 2 patterns.

Hope to have you guys's advices,

Many thanks.

Upvotes: 1

Views: 418

Answers (2)

varnika miglani
varnika miglani

Reputation: 1

I am also working on TIMIT Dataset for speaker verification. I have extracted mfcc features and trained a UBM for same, and adapted for each speaker.When it comes to adaptation I have used diagonal matrix. How are you testing the wav files? However, when it comes to features you can use pitch and energy.

Upvotes: 0

Nikolay Shmyrev
Nikolay Shmyrev

Reputation: 25220

State of the art these days is xvectors:

Deep Neural Network Embeddings for Text-Independent Speaker Verification

Implementation in Kaldi is here.

Upvotes: 1

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