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1

Application of Teager Energy Operator on Linear and Mel Scales for Whispered Speech Recognition

Marković B. R., Galić J., Mijić M.

Archives of Acoustics

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2018

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Vol. 43, No. 1

3--9

EN

This paper presents experimental results on whispered speech recognition based on Teager Energy Operator for linear and mel cepstral coefficients including the Cepstral Mean Subtraction normalization technique. The feature vectors taken into consideration are Linear Frequency Cepstral Coefficients, Teager Energy based Linear Frequency Cepstral Coefficients, Mel Frequency Cepstral Coefficients and Teager Energy based Mel Frequency Cepstral Coefficients. A speaker dependent scenario is used. For the recognition process, Dynamic Time Warping and Hidden Markov Models methods are applied. Results show a respectable improvement in whispered speech recognition as achieved by using the Teager Energy Operator with Cepstral Mean Subtraction.

2

Towards the automatic acoustical avian monitoring system

Wielgat R., Król D., Potempa T., Kozioł P., Lisowska-Lis A.

Tarnowskie Colloquia Naukowe. Nauki Techniczne i Ścisłe

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2017

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T. 4, nr 3

17--38

EN

One of the crucial aspects of the environmental protection is continuous monitoring of environment. Specific aspect is estimation of the bird species population. It is particularly important for bird species being in danger of extinction. Avian monitoring programs are time and money consuming actions which usually base on terrain expeditions. Certain remedy for this can be automatic acoustical avian monitoring system, described in the paper. Main components of the designed system are: digital audio recorder for bird voices acquisition, computer program automatically recognizing bird species by its signals emitted (voices or others) and object-relational database accessed via the Internet. Optional system components can be: digital camera and camcorder, bird attracting device, wireless data transmission module, power supply with solar panel, portable weather station. The system records bird voices and sends the recordings to the database. Recorded bird voices can be also provoked by the attracting device. Application of wireless data transmission module and power supply with solar panel allows long term operation of digital sound recorder in a hard accessible terrain. Recorded bird voices are analysed by the computer program and labelled with the automatically recognized bird species. Recognition accuracy of the program can be optionally enhanced by an expert system. Besides of labelled sound recordings, database can store also many other information like: photos and films accompanying recorded bird voices/ sounds, information about localization of observation/ recordings (GPS position, description of a place of an observation), information about bird features and behaviour, meteorological information, etc. Database on the base of geographical/ geological digital maps can generate actual maps of bird population (presence, number of individuals of each species). Moreover data-base can trigger alerts in case of rapidly decreasing bird population. It is also possible to obtain new knowledge about bird species with data mining methods. The paper presents collected data on observed bird species (audio recordings, photos and films) as well as results of experiments testing particular components of the automatic acoustical avian monitoring system.

3

FPGA implementation of logarithmic versions of Baum-Welch and Viterbi algorithms for reduced precision hidden Markov models

Pietras M., Klęsk P.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2017

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Vol. 65, nr 6

935--946

EN

This paper presents a programmable system-on-chip implementation to be used for acceleration of computations within hidden Markov models. The high level synthesis (HLS) and “divide-and-conquer” approaches are presented for parallelization of Baum-Welch and Viterbi algorithms. To avoid arithmetic underflows, all computations are performed within the logarithmic space. Additionally, in order to carry out computations efficiently – i.e. directly in an FPGA system or a processor cache – we postulate to reduce the floating-point representations of HMMs. We state and prove a lemma about the length of numerically unsafe sequences for such reduced precision models. Finally, special attention is devoted to the design of a multiple logarithm and exponent approximation unit (MLEAU). Using associative mapping, this unit allows for simultaneous conversions of multiple values and thereby compensates for computational efforts of logarithmic-space operations. Design evaluation reveals absolute stall delay occurring by multiple hardware conversions to logarithms and to exponents, and furthermore the experiments evaluation reveals HMMs computation boundaries related to their probabilities and floating-point representation. The performance differences at each stage of computation are summarized in performance comparison between hardware acceleration using MLEAU and typical software implementation on an ARM or Intel processor.

4

A System for Predicting Musculoskeletal Disorders Among Dental Students

Thanathornwong B., Suebnukarn S., Ouivirach K.

International Journal of Occupational Safety and Ergonomics

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2014

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Vol. 20, No. 3

463--475

EN

Objective. This study aimed to develop a system for predicting work-related musculoskeletal disorders (WMSD) among dental students. Materials and methods. The system comprised 2 accelerometer sensors to register neck and upper back postures and movements, and software developed to collect and process the data. Hidden Markov models (HMMs) were used to predict the likelihood of WMSD in dental students by comparing their neck and upper back movement patterns with WMSD and non-WMSD HMMs learned from previous data. To evaluate the performance of the system, 16 participants were randomly assigned into a 2 × 2 crossover trial scheduled for each sequence of working: receiving feedback or no-feedback from the system. The primary outcome measure was the extension of the neck and upper back, before (pre-test) and after (posttest) receiving feedback or no-feedback from the system. The secondary outcome measure was the log likelihood of classifying the movements as WMSD. Results and discussion. The results showed that in the group that received feedback, the extension of the neck in the y axis and of the upper back in the y axis decreased significantly (t test, p < .05) on the post-test. Conclusion. The system for predicting and preventing WMSD aids the correction of the extension of the neck and upper back in the y axis.

5

Hybrid of neural networks and hidden Markov models as a modern approach to speech recognition systems

Sokólski P., Rutkowski T.

Pomiary Automatyka Robotyka

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2013

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R. 17, nr 2

449-455

EN

The aim of this paper is to present a hybrid algorithm that combines the advantages of artificial neural networks and hidden Markov models in speech recognition for control purposes. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov models (HMM). The main part of the paper consists of a description of development and implementation of a hybrid algorithm of speech recognition using NN and HMM and presentation of verification of correctness results.

PL

Celem artykułu jest przedstawienie algorytmów hybrydowych łączących zalety sztucznych sieci neuronowych i ukrytych modeli Markowa w zastosowaniach rozpoznawania mowy dla potrzeb sterowania. W zakres opracowania wchodzi przegląd stosowanych obecnie rozwiązań, opis i analiza implementacji wybranych struktur sieci neuronowych (NN) oraz ukrytych modeli Markowa (HMM). Główną część artykułu stanowi opis opracowywania hybrydowego algorytmu rozpoznawania mowy wykorzystującego NN i HMM oraz prezentacja wyników weryfikacji poprawności działania.

6

A novel text classification problem and its solution

Zadrożny S., Kacprzyk J., Gajewski M., Wysocki M.

Czasopismo Techniczne. Automatyka

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2013

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R. 110, z. 4-AC

7--16

EN

A new text categorization problem is introduced. As in the classical problem, there is a set of documents and a set of categories. However, in addition to being assigned to a specific category, each document belongs to a certain sequence of documents, referred to as a case. It is assumed that all documents in the same case belong to the same category. An example may be a set of news articles. Their categories may be sport, politics, entertainment, etc. In each category there exist cases, i.e., sequences of documents describing, for example evolution of some events. The problem considered is how to classify a document to a proper category and a proper case within this category. In the paper we formalize the problem and discuss two approaches to its solution.

PL

W artykule proponuje się nowe zadanie kategoryzacji dokumentów tekstowych. Podobnie jak w zadaniu klasycznym rozważa się zbiór dokumentów tekstowych i zbiór kategorii. W odróżnieniu od zadania klasycznego, dokumenty są przypisane nie tylko do kategorii, ale również do określonej sekwencji dokumentów w ramach danej kategorii, zwanej sprawą. Zakłada się, że wszystkie dokumenty danej sprawy należą do tej samej kategorii. Przykładem może być kolekcja wiadomości prasowych. Mogą one należeć do kategorii takich, jak sport, polityka, rozrywka itp. W ramach każdej kategorii występują sekwencje wiadomości (sprawy) opisujące np. rozwój pewnych zdarzeń. Zadanie polega więc na zaklasyfikowaniu dokumentu do właściwej kategorii i właściwej sprawy w jej ramach. W artykule formalnie definiuje się nowe zadanie kategoryzacji i proponuje się dwa podejścia do jego rozwiązania.

7

Using hidden Markov models in signature recognition process

Doroz R., Wróbel K.

Journal of Medical Informatics & Technologies

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2012

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Vol. 21

75--84

EN

This paper presents a method of recognition of handwritten signatures with the use of Hidden Markov Models (HMM). The method in question consists in describing each signature with a sequence of symbols. Sequences of symbols were generated on the basis of an analysis of local extremes determined on diagrams of dynamic features of signatures. For this purpose, the method proposed by G.K. Gupta and R.C. Joyce has been modified. The determined sequences were then used as input data for the HMM method. The studies were conducted with the use of the SVC2004 database. The results are competitive in relation to other methods known from the literature.

8

Tunneling Activities Detection Using Machine Learning Techniques

Allard F., Dubois R., Gompel P., Morel M.

Journal of Telecommunications and Information Technology

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2011

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nr 1

37-42

EN

Tunnel establishment, like HTTPS tunnel or related ones, between a computer protected by a security gateway and a remote server located outside the protected network is the most effective way to bypass the network security policy. Indeed, a permitted protocol can be used to embed a forbidden one until the remote server. Therefore, if the resulting information flow is ciphered, security standard tools such as application level gateways (ALG), firewalls, intrusion detection system (IDS), do not detect this violation. In this paper, we describe a statistical analysis of ciphered flows that allows detection of the carried inner protocol. Regarding the deployed security policy, this technology could be added in security tools to detect forbidden protocols usages. In the defence domain, this technology could help preventing information leaks through side channels. At the end of this article, we present a tunnel detection tool architecture and the results obtained with our approach on a public database containing real data flows.

9

Praktyczne aspekty wykorzystywania systemów rozpoznawania mowy opartych na HMM

Mietła A., Iwaniec M.

Modelowanie Inżynierskie

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2010

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T. 9, nr 40

171-178

PL

W artykule poruszono problem tworzenia systemów automatycznego rozpoznawania mowy zbudowanych na bazie ukrytych modeli Markowa. Przedstawiono matematyczne podstawy HMM oraz odniesiono je do rzeczywistego problemu. Wykazano, że niezwykle istotny jest odpowiedni dobór liczby stanów oraz rozkładów w systemie. Zaprezentowano także wyniki testów stwierdzające przewagę współczynników RASTA-PLP nad MFCC oraz konieczność stosowania parametrów delta oraz delta-delta.

EN

Article discusses problems associated with automatic speech recognition systems based on Hidden Markov Model. Mathematical basis of HMM have been presented and it is shown how it can be applied to the real problem. Extremely important is the proper selection of the quantity of states and Gaussian distributions. Test results indicating the advantage of RASTA-PLP coefficients over MFCCs and necessity of using delta and delta-delta parameters are presented.

10

Selection of parameters of HMM

Bobulski J.

Pomiary Automatyka Kontrola

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2009

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R. 55, nr 10

844-846

EN

Hidden Markov models are widely applied in data classification. They are used in many areas. The choice of parameters of HMM is very important because of efficiency of whole identification system. Individual parameters should be matched individually for each system in the experiment way.

PL

Ukryte modele Markowa (ang. Hidden Markov Models - HMM) są szeroko stosowane do klasyfikacji danych w wielu dziedzinach, np. w biometryce do rozpoznawania twarzy lub głosu, rozpoznawania obrazów i dźwięku. Pozwala to na budowanie skutecznych systemów kontroli dostępu do zasobów oraz systemów identyfikacji/autoryzacji osób. Każde z tych zastosowań wymaga specyficznego podejścia do problemu i odpowiedniego zaprojektowania HMM. Dobór Parametrów HMM jest bardzo ważny ze względu za skuteczność systemu identyfikacji. Poszczególne parametry powinny być dobierane indywidualnie dla każdego systemu w sposób eksperymentalny, a badania powinny być przeprowadzone na reprezentatywnej liczbie wzorców. Najważniejszym problemem w projektowaniu systemów opartych o HMM jest wybór architektury modelu, czyli topologii oraz liczby stanów i obserwacji. Wpływ na te parametry ma złożoność i zróżnicowanie danych- sygnałów wejściowych. W przypadku topologii do dyspozycji mamy modele ergodyczne lub left-right. Natomiast przy doborze liczby stanów i obserwacji uwzględniamy typ sygnału wejściowego. Im bardziej złożony i różnorodny, tym te wartości powinny być większe. Należy jednak pamiętać, że im więcej stanów i obserwacji wybierzemy, tym czas estymacji parametrów i czas testowania wydłuży się wykładniczo. Ponadto istnieje granica, powyżej której system nie będzie wykazywał większej skuteczności.

11

Wykorzystanie metod optymalizacyjnych do budowania ukrytych modeli Markowa w analizie danych z mikromacierzy DNA

Walawender P., Ćmielowski Ł.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2009

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Vol. 15, nr 1

11-13

PL

Techniki mikromacierzy DNA umożliwiły pomiar ekspresji genów i obserwowanie zależności między tkankami z różnych próbek. W artykule omówiono zastosowanie algorytmów opartych na ukrytych modelach Markowa (ang. Hidden Markov Models) do analizy danych z mikromacierzy DNA. Zaprezentowane podejście porównano z innymi, opisanymi w podobnych opracowaniach. Zaproponowane algorytmy składają się z dwóch części: odkrywczej i klasyfikacyjnej. Za pomocą zbioru danych treningowych stworzono uniwersalny klasyfikator, którego efektywność i inne parametry będą mierzone za pomocą danych testowych.

EN

DNA microarray technologies make possible measurement of genes expression and observation the differences between various tissue samples. The application of hidden Markov models for analyzing DNA microarrays gene expression data, will be reported. A new approach will be compared with similar approaches used in other publications. The proposed algorithms will be composed of two parts: discovery and classification. By means of training data an universal classifier will be created, which efficiency as well as other parameters will be measured by testing data.

12

O Ukrytych Modelach Markowa i ich zastosowaniu do rozpoznawania ciągów znaków pisma odręcznego

Klęsk P.

Metody Informatyki Stosowanej

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2008

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nr 1 (Tom 13)

175-189

EN

In the paper, selected informations on Hidden Markov Models (also called Hidden Markov Chains) are reminded. Basic riotions are defined and algorithms related to these models are shortly presented. The research part of the papers shows results of three conducted experiments entitled: "pork cutlet", "form sheet" and ''poetaster". The most important experiment "form sheet" gives a good starting point to a practical application of HMMs to the. handwriting recognition. The "poetaster" experiment shows possible application of HMMs in so called "artifial creation".

13

Mixed parametrization method of quality improvement in speech commands recognition system for Polish

Wydra S.

Poznan University of Technology Academic Journals. Electrical Engineering

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2007

|

No 54

205-212

EN

This paper discusses a mixed parameterisation modelling method in a speaker independent Automatie Speech Recognition (ASR) system Tor Polish keywords. The goal of this project is to improve the recognition quality in Polish commands and instructions recognition system based on mel-frequency cepstrum coefficients (MFCC) modelling. In this project we studied the recognition quality using a mixed speech modelling consisting of MFCC and prosodic parameters. We experimentally showed that the mixed modelling yields belter recognition quality than a simple MFCC modelling.

14

The method of user's identification using the fusion of wavelet transform and hidden Markov Models

Bobulski J.

Computing, Multimedia and Intelligent Techniques

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2005

|

Vol. 1 nr 1

173-179

EN

The work concerns creation of the original FaMar method of user's identification on the basis of the frontal facial image, in which the fusion of Wavelet Transformation (WT) and Hidden Markov Models (HMM) are used for the three parts of face (eyes, nose, mouth); the decision is made on the basis of the sum maximalisation of likelihood of generating of the models observation.

15

Automatic recognition of signed Polish expressions

Kapuściński T., Wysocki M.

Archives of Control Sciences

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2005

|

Vol. 15, no. 3

329-336

EN

The paper considers recognition of single sentences of the Polish Sign Language. We use a canonical stereo system that observes the signer from a frontal view. Feature vectors take into account information about the hand shape and orientation, as well as 3D position of the hand with respect to the face. Recognition based on human skin detection and hidden Markov models (HMMs) is performed on line. We focus on 35 sentences and a 101 word vocabulary that can be used at the doctor's and at the post office. Details of the solution and results of experiments with regular and parallel HMMs are given.

16

Tagowanie i dezambiguacja morfosyntaktyczna : przegląd metod i oprogramowania

Dębowski Ł.

Prace Instytutu Podstaw Informatyki Polskiej Akademii Nauk

|

2001

|

Nr 934

1-31

PL

Przedstawiono aktualne metody i dostępne oprogramowanie do automatycznego tagowania i uczenia się tagerów. Omówiono skuteczność zastosowań przedstawionych metod i oprogramowania do dezambiguacji morfosyntaktycznej tekstów w językach naturalnych.

EN

We present state-of-the-art methods and available software for automatic tagging and tagger learning. Furthermore, we discuss applicability of presented methods and software for morphosyntactic disambiguation of texts in natural languages.

17

Hidden Markov Model (HMM) - opis modelu i algorytmów pod kątem wykorzystania w problemach rozpoznawania mowy i pisma

Gąciarz T.

Elektrotechnika i Elektronika

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1998

|

T. 17, nr 1

17--31

EN

The use of hidden Markov models (HMM's) for speech and handwriting recognition has become increasingly popular in the past few years. The reason why this method has become so popular are: the inherent statistical (mathematically precise) framework, the easy and availability of training algorithms for estimating the parameters of the models from the finite training sets of data, the flexibility of the resulting recognition system where one can easily change the size, type, or architecture of the models to suit particular words, sounds etc., and the ease of implementation of the overall recognition system. In this paper, the basic information on hidden Markoy model is presented. It includes formal description of the model, methods and algorithms used for training and recognition.

PL

Hidden Markov Model już od kilkunastu lat cieszy się niesłabnącą popularnością w zastosowaniach związanych z rozpoznawaniem mowy i pisma ręcznego. Przyczyną tak wielkiej popularności są niewątpliwie solidnie opracowane podstawy matematyczne modelu (teoria), jak i struktura implementacyjna (praktyka). Wykorzystywane, ogólnie dostępne algorytmy charakteryzują się jasnością i efektywnością estymacji parametrów modelu na podstawie skończonego zbioru uczącego. Elastyczność systemu rozpoznawania pozwala na łatwe dostosowanie rozmiaru, typu i architektury modelu do odpowiednich słów, dźwięków itp. W artykule tym zawarto podstawowe dane na temat budowy HMM wraz z jego formalnym opisem. Przedstawiono także ideę działania najbardziej znanych algorytmów służących do uczenia i rozpoznawania z wykorzystaniem modelu.