Building LSTM neural network based speaker identification system

Laurynas Dovydaitis, Vytautas Rudžionis


In this paper, we are analyzing the results of native Lithuanian speaker recognition and identification using long short-term memory deep neural network. We look at recognition accuracy and identify further potential improvements. Dataset used for training and speaker recognition consists of over 370 unique speakers, who provide their voice utterances in Lithuanian language. In this paper we present results that are derived from part of this dataset.

DOI: 10.15181/csat.v6i1.1579


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