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Speaker Recognition in the VoIP Environment
Remeš, Jan ; Pešán, Jan (referee) ; Plchot, Oldřich (advisor)
Tato práce popisuje použití systémů pro rozpoznávání mluvčího v~prostředí VoIP, úspěšnost systému a přístupy k jejímu zlepšení. Popisuje architekturu těchto systémů, metriky pro vyhodnocení jejich úspěšnosti a klíčové komponenty VoIP z hlediska rozpoznávání mluvčího. Je zde popsáno vytvoření simulace VoIP prostředí, úspěšnost systému je vyhodnocena na datech pocházejících z různých druhů VoIP prostředí a výsledky jsou demostrovány. Adaptace a kalibrace systému je provedena a jejich přínosy zhodnoceny.
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Computer Graphics and Video Features for Speaker Recognition
Fér, Radek ; Matějka, Pavel (referee) ; Černocký, Jan (advisor)
We describe a non-traditional method for speaker recognition that uses features and algorithms used mainly for computer vision. Important theoretical knowledge of computer recognition is summarized first. The Boosted Binary Features are described and explored as an already proposed method, that has roots in computer vision. This method is evaluated on standard speaker recognition databases TIMIT and NIST SRE 2010. Experimental results are given and compared to standard methods. Possible directions for future work are proposed at the end.
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Text Dependent Speaker Verification
Fux, Jan ; Glembek, Ondřej (referee) ; Matějka, Pavel (advisor)
The goal of this Bachelor's thesis was to design text dependent speaker recognition system. There were few systems tested for MIT database. This database contains recordings of 0.46s average length. Best case for recognition is to use a combination of DTW system using posterior probability estimation (posteriograms) as an output of Phoneme recognizer and acoustic SID system based on iVectors and PLDA (Probabilistic Linear Component Analysis). Fusion with Neural network gives the best results (EER). These are 17.84% EER for women and 16.38% for men. It's 49.9% relative improvement for women and 54.2% for men against acoustic recognition alone.
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Speaker Recognition Based on Long Temporal Context
Fér, Radek ; Matějka, Pavel (referee) ; Černocký, Jan (advisor)
Tato práce se zabývá extrakcí vhodných příznaků pro rozpoznávání řečníka z delších časových úseků. Po představení současných technik pro extrakci takových příznaků navrhujeme a popisujeme novou metodu pracující v časovém rozsahu fonémů a využívající známou techniku i-vektorů. Velké úsilí bylo vynaloženo na nalezení vhodné reprezentace temporálních příznaků, díky kterým by mohly být systémy pro rozpoznávání řečníka robustnější, zejména modelování prosodie. Náš přístup nemodeluje explicitně žádné specifické temporální parametry řeči, namísto toho používá kookurenci řečových rámců jako zdroj temporálních příznaků. Tuto techniku testujeme a analyzujeme na řečové databázi NIST SRE 2008. Z výsledků bohužel vyplývá, že pro rozpoznávání řečníka tato technika nepřináší očekávané zlepšení. Tento fakt diskutujeme a analyzujeme ke konci práce.
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Adaptation of Speaker Recognition Systems
Novotný, Ondřej ; Pešán, Jan (referee) ; Plchot, Oldřich (advisor)
In this paper, we propose techniques for adaptation of speaker recognition systems. The aim of this work is to create adaptation for Probabilistic Linear Discriminant Analysis. Special attention is given to unsupervised adaptation. Our test shows appropriate clustering techniques for speaker estimation of the identity and estimation of the number of speakers in adaptation dataset. For the test, we are using NIST and Switchboard corpora.
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Modelling Prosodic Dynamics for Speaker Recognition
Jančík, Zdeněk ; Fapšo, Michal (referee) ; Matějka, Pavel (advisor)
Most current automatic speaker recognition system extract speaker-depend features by looking at short-term spectral information. This approach ignores long-term information. I explored approach that use the fundamental frequency and energy trajectories for each speaker. This approach models prosody dynamics on single fonemes or syllables. It is known from literature that prosodic systems do not work as well the acoustic one but it improve the system when fusing. I verified this assumption by fusing my results with state of the art acoustic system from BUT. Data from standard evaluation campaigns organized by National Institute of Standarts and Technology are used for all experiments.
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Identification of persons via voice imprint
Mekyska, Jiří ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
This work deals with the text-dependent speaker recognition in systems, where just a few training samples exist. For the purpose of this recognition, the voice imprint based on different features (e.g. MFCC, PLP, ACW etc.) is proposed. At the beginning, there is described the way, how the speech signal is produced. Some speech characteristics important for speaker recognition are also mentioned. The next part of work deals with the speech signal analysis. There is mentioned the preprocessing and also the feature extraction methods. The following part describes the process of speaker recognition and mentions the evaluation of the used methods: speaker identification and verification. Last theoretically based part of work deals with the classifiers which are suitable for the text-dependent recognition. The classifiers based on fractional distances, dynamic time warping, dispersion matching and vector quantization are mentioned. This work continues by design and realization of system, which evaluates all described classifiers for voice imprint based on different features.
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Demontration System for Speaker Recognition
Šústek, Martin ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
My diploma theses deals with the problem of the speaker recognition. The basic theory of this problem is described in the text as well as model and implementation of the system for speaker recognition. The scope of the system is to recognize up to three speakers. The theory is based on calculation parameters for speaker recognition and processing of voice. Program is made in Matlab as a independent application and it has got Czech and English interface.
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Neural networks in speaker classification
Svoboda, Libor ; Atassi, Hicham (referee) ; Míča, Ivan (advisor)
The content of this work is focused on the neural network per speaker recognition. The work deals with problems of processing speech signal and there are introduction some types of neural network. The part of work was made database of records from speakers with have various sex and ages. The train and test group was made from the database. For classifier were suggested afterwards. One of them was nominated on base Gaussian mixture model and three of them were nominated on neural. This system was tested and analyzed on the basis of age, gender and both criterions each other at the end. Attention is focused on choice suitable feature in each mission of classification at the same time. At the end of work are introduced results of analysis for individual groups and features. The most suitable features are diagnosed from given mission of classification and the most prosperous classifier.
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