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A Look Up Table-free Gaussian Mixture Model-based Speaker Classifier

Alberto Gianelli

A Look Up Table-free Gaussian Mixture Model-based Speaker Classifier.

Rel. Mariagrazia Graziano. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2018

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Abstract:

In this thesis an ASIC design of an hardware GMM-Based Speaker Classifier is presented. The Classifier is a fundamental component of a Speaker Identification system, that is able to associate an unknown incoming speech signal to its unknown speaker, which is part of a previously modeled group of speakers. The design flow fol- lows a software-to-hardware approach, since the whole system is firstly implemented in Matlab, then increasingly transformed from high-level to machine-level until its hardware description. Innovative techniques that avoid any memory accesses to per- form hardware exponentials and logarithms are presented. All the computations are executed on-chip and this gives extra performances and extra security to the system. Thanks to its low power demand, it is suitable to be integrated in many IoT devices to personalize the user experience without compromising the power budget of the device.

Relatori: Mariagrazia Graziano
Anno accademico: 2018/19
Tipo di pubblicazione: Elettronica
Numero di pagine: 83
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-29 - INGEGNERIA ELETTRONICA
Ente in cotutela: UNIVERSITY OF ILLINOIS AT CHICAGO (STATI UNITI D'AMERICA)
Aziende collaboratrici: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/9562
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