Accuracy research using neural networks for speaker idenfitification
Abstract
In this paper we present results on speaker identification task by using neural networks for acoustic modelling. Article is structured by describing speaker identification workflow, later identifying specific steps needed for speaker identification. Afterwards we identify number of different neural network configurations which can be used for speaker identification.
Article in Lithuanian.
Diktoriaus identifikavimo tikslumo tyrimas naudojant neuroninius tinklus
Santrauka
Šiame straipsnyje nagrinėjami kai kurie diktoriaus identifikavimo problemos aspektai. Problemos aktualumas nulemtas praktinių galimybių suteikti adaptuotas paslaugas konkrečiam asmeniui, žinant jo tapatybę. Straipsnyje aprašoma diktoriaus identifikavimo veiksmų seka ir išskiriami identifikavimo etapai. Apžvelgiami moksliniai akustinių modelių kūrimo darbai pasitelkiant neuroninius tinklus. Šiame straipsnyje siūlomos kelios neuroninių tinklų konfigūracijos, kurios gali būti naudojamos diktoriaus akustiniam modeliavimui. Teikiami pasiūlymai eksperimentiniu būdu patikrinami fiksuojant gaunamą diktoriaus identifikavimo tikslumą su LIEPA projekto metu surinktu garsynu.
Reikšminiai žodžiai: diktoriaus identifikavimas, neuroniniai tinklai, GRU, BGRU, LSTM, BLSTM, MFCC.
Keyword : speaker identification, neural nets, GRU, BGRU, LSTM, BLSTM, MFCC
This work is licensed under a Creative Commons Attribution 4.0 International License.
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