Skip to content

Detail of publication


Zbyněk Zajíc : Adaptace akustického modelu v úloze s malým množstvím adaptacních dat . 2012.

Download PDF



This work is focused on the automatic speaker adaptation of an acoustic model, which is a part of the automatic speech recognition system. To train the acoustic model it is necessary to have large amount of data from many speakers. The final speaker-independent model is then able to recognize the speech from any speaker. The speaker-independent model is adapted to the speech of a specific speaker. Ordinary adaptation techniques introduced in this work perform poorly in cases with insufficient amount of adaptation data. The aim of this work is to discuss methods of adaptation and adaptation training. To avoid the problem with lack of adaptation data various robust solutions have been described and new one have been proposed. Some of these methods were tested, and the experiments show that the robust adaptation contributes significantly to the task of automatic speech recognition.

Detail of publication

Title: Adaptace akustického modelu v úloze s malým množstvím adaptacních dat
Author: Zbyněk Zajíc
Language: Czech
Year: 2012
Type of publication: Habilitation and dissertation theses
/ 2013-02-18 16:37:09 /


Adaptation, ann, FA, EV, MLLR, MAP


 author = {Zbyn\v{e}k Zaj\'{i}c},
 title = {Adaptace akustick\'{e}ho modelu v \'{u}loze s mal\'{y}m mno\v{z}stv\'{i}m adaptacn\'{i}ch dat},
 year = {2012},
 url = {},