  This paper describes our solution for the Diarization of Speaker and Language
in Conversational Environments Challenge (Displace 2023). We used a combination
of VAD for finding segfments with speech, Resnet architecture based CNN for
feature extraction from these segments, and spectral clustering for features
clustering. Even though it was not trained with using Hindi, the described
algorithm achieves the following metrics: DER 27. 1% and DER 27. 4%, on the
development and phase-1 evaluation parts of the dataset, respectively.
