A library for the Unbounded Interleaved-State Recurrent Neural Network algorithm
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.
This algorithm was originally proposed in the paper
Fully Supervised Speaker Diarization.
The work has been introduced by
Google AI Blog.
Disclaimer
This open source implementation is slightly different than the internal one
which we used to produce the results in the
paper, due to dependencies on
some internal libraries.
We CANNOT share the data, code, or model for the speaker recognition system
(d-vector embeddings)
used in the paper, since the speaker recognition system
heavily depends on Google’s internal infrastructure and proprietary data.
This library is NOT an official Google product.
We welcome community contributions (guidelines)
to the uisrnn/contrib folder.
But we won’t be