The number of speakers and whether the content of the speaker needs to be the same。 - Githubissues

google / uis-rnn

This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.

https://arxiv.org/abs/1810.04719

Apache License 2.0

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The number of speakers and whether the content of the speaker needs to be the same。 #49

Closed zyc1310517843 closed 5 years ago

zyc1310517843 commented 5 years ago

Describe the question

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My background

Have I read the README.md file?

yes/no - if you answered no, please stop filing the issue, and read it first

Have I searched for similar questions from closed issues?

yes/no - if you answered no, please do it first

Have I tried to find the answers in the paper Fully Supervised Speaker Diarization?

yes/no

Have I tried to find the answers in the reference Speaker Diarization with LSTM?

yes/no

Have I tried to find the answers in the reference Generalized End-to-End Loss for Speaker Verification?

yes/no Hello, preparations have been completed. Now we want to train our voice data. I want to ask three questions: 1. How many speakers do we need at least? 2. How long does each speaker need to say a few words? 3. Does each speaker need to speak the same sentence? Thank you for your guidance.

wq2012 commented 5 years ago

Please find the answers in the above mentioned papers.