Wyniki wyszukiwania - Biblioteka Nauki

1

A Vibroacoustic Model of Selected Human Larynx Diseases

100%

Engel Z. W. , Kłaczyński M. , Wszołek W.

International Journal of Occupational Safety and Ergonomics

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2007

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tom Vol. 13, No. 4

367--379

EN

With the present development of digital registration and methods for processing speech it is possible to make effective objective acoustic diagnostics for medical purposes. These methods are useful as all pathologies and diseases of the human vocal tract influence the quality of a patient’s speech signal. Diagnostics of the voice organ can be defined as an unambiguous recognition of the current condition of a specific voice source. Such recognition is based on an evaluation of essential acoustic parameters of the speech signal. This requires creating a vibroacoustic model of selected deformations of Polish speech in relation to specific human larynx diseases. An analysis of speech and parameter mapping in 29-dimensional space is reviewed in this study. Speech parameters were extracted in time, frequency and cepstral (quefrency) domains resulting in diagrams that qualified symptoms and conditions of selected human larynx diseases. The paper presents graphically selected human larynx diseases.

2

Study of effects of surgical treatment in the larynx area on the speech signal

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Wszołek W. , Kłaczyński M. , Modrzejewski M.

Archives of Acoustics

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2008

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tom Vol. 33, No. 4

497-508

EN

The speech signal emitted by humans may be a source of useful diagnostic and prognostic information. The signal may become, indirectly by some selected parameters, an additional source of information concerning the condition of the patient's vocal tract anatomy, as well as physiology and pathology (deformation) of his/her other internal organs. The paper presents the next, consecutive stage of the authors' research, concerning the search for additional parameters, which could be used for objective detection and registration of pathological changes in the larynx and vocal tract area.

3

Rule Based Speech Signal Segmentation

100%

Greibus M. , Telksnys L.

Journal of Telecommunications and Information Technology

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2010

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tom nr 4

37-43

EN

This paper presents the automated speech signal segmentation problem. Segmentation algorithms based on energetic threshold showed good results only in noise-free environments. With higher noise level automatic threshold calculation becomes complicated task. Rule based postprocessing of segments can give more stable results. Off-line, on-line and extrema types of rules are reviewed. An extrema-type segmentation algorithm is proposed. This algorithm is enhanced by a rule base to extract higher energy level segments from noise. This algorithm can work well with energy like features. The experiments were made to compare threshold and rule-based segmentation in different noise types. Also was tested if multifeature segmentation can improve segmentation results. The extrema rule-based segmentation showed smaller error ratio in different noise types and levels. Proposed algorithm does not require high calculation resources. Such algorithm can be processed by devices with limited computing power.

4

Research on the changes in voice quality caused by tonsillectomy

100%

Potępa Ł. , Tadeusiewicz R. , Szaleniec J.

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2012

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tom Vol. 8, no. 1

159--173

EN

The article presents the results of the research on the changes in voice quality caused by tonsillectomy. It was carried out in a group of 20 patients (12 male and 8 female). The voice was recorded on a E-MU 0404 USB sound card with a 24-bit A/C AK5385A convertor. Having analyzed the pronunciation of prolonged Polish vowels: /a/, /e/, /i/ and /u/, the researchers defined a set of parameters which differentiate the pronunciation before and after tonsillectomy. The results show that the differences in pronunciation might be observed due to dynamic properties of the articulatory track. Additional researches emphasize the usefulness of such recordings applying external E-MU 0404 USB sound card in the clinical environment.

5

Baza danych nagrań mowy dla analizy porównawczej różnojęzycznych fonemów

100%

Mąsior M. , Igras M. , Ziółko M. , Kacprzak S.

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tom Vol. 34, nr 2B

79--87

PL

Artykuł prezentuje system gromadzenia, archiwizacji i akustycznej analizy wielojęzycznych próbek mowy. Głównym celem badań jest analiza porównawcza fonemów dla kilkuset języków i stworzenie drzewa genealogicznego języków świata. Opisana została implementacja systemu, jako bazy danych z portalem internetowym. Przedstawiono informacje dotyczące zawartości i formy bazy, perspektyw rozwoju i zastosowań w lingwistyce komputerowej.

EN

The paper presents a system of collecting and analyzing multilanguage speech samples for research on characteristics of phonemes in several hundred world languages. We describe the implementation: database and webpage. The content and form of the database and applications for development of the new methods of speech analysis are presented.

6

Application of new acoustic parameters in ANN-aided pathological speech diagnosis

88%

Szaleniec J. , Modrzejewski M. , Szaleniec M. , Wszołek W.

Archives of Acoustics

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2007

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tom Vol. 32, No. 1

177-186

EN

Most diseases of the vocal tract cause changes in the voice quality. Acoustic analysis of the speech signal is a widely used, noninvasive, objective and low-cost method of laryngeal pathology recognition and classification. There have been numerous attempts [1-3] to develop an automatic system which could aid the laryngological diagnosis. The goal of the presented research is to verify, whether the new approach to the acoustic analysis and parameters introduced in the Voice Analysis and Screening System (VASS 3.0 [4]) such as turbulence noise index (TNI) and normalized first harmonic energy (NFHE), can improve the effectiveness of automated diagnosis. The automated diagnosis was performed using Artificial Neural Networks (ANN). Multilayer perceptron and radial basis function neural networks of various architectures were trained to classify between pathologic and non-pathologic voices, while the parameters computed with VASS were used as input data. Preliminary results show that the Voice Analysis and Screening System coupled with ANN can be a highly effective tool for ANN-aided pathological speech diagnosis.

7

Fusing the electromagnetic articulograph, high-speed video cameras and a 16-channel microphone array for speech analysis

88%

Mik Ł. , Lorenc A. , Król D. , Wielgat R. , Święciński R. , Jędryka R.

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8

Methods of deformed voice signal evaluation after larynx surgery

75%

Wszołek W. , Kłaczyński M.

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tom Vol. 28, no. 1

31-37

EN

In the work has been shown from studies concerning the application of modified acoustic signal processing methods to the task of evaluation and classification of larynx surgery effects. The goal of the standard speech recognition studies is to reveal the semantic aspects of the pronounced text. In the tasks of medical diagnosis employing the speech signal analysis the semantic aspects are insignificant. The required signal characteristics should be as sensitive as possible to small deformations of the layers directly related to the voice functioning and the structure of vocal tract. The goal of the work is presentation of voice quality after various surgical treatments, performed in the ENT area. The research subject is the speech articulation process itself and all its pathological deformations, which determines both the used signal analysis tools as well as the techniques of the selected objects recognition, which are the forms of the particular ill person speech deformation forms in comparison to the speech of the whole sound people population. The evaluation has been carried out both for voice quality after larynx surgery as well as voice quality after surgical treatment of resonance cavities (nose, paranasal sinussis). The study was oriented towards the construction of systems based on the analysis of objectively registered acoustic signals of deformed speech.

PL

W pracy przedstawiono badania dotyczące metod przetwarzania sygnału akustycznego do oceny i klasyfikacji mowy po zabiegach w obrębie kanału głosowego. W zagadnieniach rozpoznawania mowy, problem dotyczy ujawniania semantycznych aspektów wypowiedzi. Natomiast w zagadnieniach diagnostyki medycznej przy wykorzystaniu sygnału mowy, cechy semantyczne są nieistotne. Poszukiwane cechy sygnału mowy winny być wrażliwe na małe deformacje, które mogą wystąpić w poszczególnych warstwach kanału głosowego. Celem pracy jest ocena jakości głosu po różnorodnych zabiegach chirurgicznych wykonanych w obszarze kanału głosowego. Tematem badań jest zarówno sam proces artykulacji mowy, jak i jego patologiczne deformacje. Diagnostykę narządu głosu można określić jako jednoznaczne rozpoznanie cech aktualnego stanu źródła głosu na podstawie zespołu istotnych cech akustycznych, zwartych w sygnale akustycznym. Ocena jakości głosu została przeprowadzona dla osób po chirurgicznym leczeniu krtani, nosa oraz zatok przynosowych. Badania zostały ukierunkowane na stworzenie systemu analizy umożliwiającego obiektywne rozpoznawanie deformacji sygnału mowy.

9

Selected methods of pathological speech signal analysis

75%

Wszołek W.

Archives of Acoustics

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2006

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tom Vol. 31, No. 4

413-430

EN

Selected results of examinations, having been performed by the author for several years, concerning the evaluation of selected methods of transforming signal in analysis tasks and pathological speech evaluation usability were presented in the article. In many issues of medical diagnosis, as well as in the planning of some illnesses therapy and rehabilitation, it is necessary to evaluate the signal of deformed speech. This evaluation can concern evaluation of the signal deformation degree and in this case the task is to present in a quantitative dimension (preferably scalar) the measure of deviation between the measured pathological speech signal and the abstract signal, which can be acknowledged as a pattern of the correct speech. Possessing such a scalar measurement, of the considered signal deformation degree, enables to monitor the illness process development or remission, which has a key importance in the current monitoring of the therapy effects or/and many illnesses rehabilitation. Pathological speech evaluation can also go into the direction of a classification and determination of a type of the analysed signal, which can, in some cases, have a direct connection with anatomical and functional causes as well as conditions of the considered illness. The classification of pathological speech signals can facilitate the diagnosis by pointing the most probable causes of the speech signal pathological deformation. Such a classification can also help in the optimal therapy selection and in determining rehabilitation recommendations. The methods of transformation, analysis, classification and speech signal recognition have been known apparently for many years, as with no difficulty, many writings discussing these concepts and presenting results concerning both basic examinations results and many application works, can be found. The problem, presented in this article, is strongly different from the majority of works, which were published by other authors, as most of well known works, concerning the speech signal analysis (etc.), are directed to understand the content of the statement (automatic speech understanding, a speech-writing conversion, steering of the devices by speech signal), or relatively by determining the identity of the speaker (automatic identification or authentification of the speaker). Meanwhile, in the pathological speech analysis the semantic statement content is not essential; it is also not important who the speaker is. The research subject is the speech articulation process itself and all its pathological deformations, which determines both the used signal analysis tools as well as the techniques of the selected objects recognition, which are the forms of the particular ill person speech deformation forms in comparison to the speech of the whole sound people population [5].

10

Automatic understanding of acoustic speech signal pathology

75%

Wszołek W.

Archives of Acoustics

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2007

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tom Vol. 32, No. 1

147-163

EN

In this work, parts of the research concerning a new concept of applying computer technique in pathological speech analysis have been presented. This new concept assumes that during the pathological speech analysis we are not aiming neither at the establishing of such or other signal parameters nor at the trying to classify them, but we tend to understand automatically the causes of deformation, which can be observed in the considered signal. Therefore the concept presented postulates the replacing the well known process of the pathological speech acoustic signal recognition by a more advanced method of analysis, which means a confrontation of the features, which are revealed in the signal during its transformation with features that could be expected basing on the knowledge gathered in the system concerning pathological factors deforming the true form of the signal. In the meaning of the term "automated understanding", this denotes a signal analysis of a deformed speech, which is oriented towards revealing the sources of the observed signal distortions, and not towards bare analysis of their patterns and diagnostic deduction based on their typology. In the work the basic elements of the proposed method are presented. Examples showing its essence were derived basing on the selected larynx pathology analysis.

11

Charakterystyki behawioralne w biometrii

75%

Kamińska D. , Sapiński T. , Pelikant A.

Elektronika : konstrukcje, technologie, zastosowania

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2015

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tom Vol. 56, nr 10

38-40

PL

W artykule omówiono sposoby pozyskiwania, przetwarzania i reprezentacji sygnałów audio w celu prowadzenia dalszych analiz związanych zarówno z semantyką wypowiedzi, jak również z cechami behawioralnymi mówcy. Przyjęto, że analiza danych powinna być prowadzona możliwie blisko miejsca ich przechowywania, np. w komercyjnych serwerach baz danych z wykorzystaniem enkapsulacji klas obiektowych do elementów programistycznych relacyjnego serwera. Poza wykorzystaniem reprezentacji sygnału za pomocą wektorów wyrażonych w skalach cepstralnych, ważnym elementem analizy jest zastosowanie algorytmów dopasowania strumieni wektorów danych – Spring DTW. W przypadku analizy stanów emocjonalnych do wzmocnienia procesu klasyfikacji zastosowano komitety klasyfikatorów działających na różnych zestawach atrybutów, a analizę odniesiono do modelu Plutchika.

EN

The article describes methods of acquisition, processing and representation of audio signals for the purpose of further analysis associated with both the semantics of expression, as well as behavioral characteristics of the speaker. It is assumed that the data analysis should be carried out as close to the place of storage, eg. in commercial database servers using the encapsulation of object classes to relational server software components. In addition to using a representation of a signal as vectors in cepstral scale, an important part of the analysis is to apply matching algorithms - Spring DTW. In order to enhance the analysis of emotional states classification committees consiting of classifiers operating on different sets of attributes were used. Emotion detection was based on Plutchik’s wheel.

12

Speech Analysis as a Tool for Detection and Monitoring of Medical Conditions : A review

75%

Igras-Cybulska M. , Hemmerling D. , Ziółko M. , Datka W. , Stogowska E. , Kucharski M. , Rzepka R. , Ziółko B.

Archives of Acoustics

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2023

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tom Vol. 48, No. 3

289--315

EN

The goal of this article is to present and compare recent approaches which use speech and voice analysis as biomarkers for screening tests and monitoring of some diseases. The article takes into account metabolic, respiratory, cardiovascular, endocrine, and nervous system disorders. A selection of articles was performed to identify studies that assess voice features quantitatively in selected disorders by acoustic and linguistic voice analysis. Information was extracted from each paper in order to compare various aspects of datasets, speech parameters, methods of applied analysis and obtained results. 110 research papers were reviewed and 47 databases were summarized. Speech analysis is a promising method for early diagnosis of certain disorders. Advanced computer voice analysis with machine learning algorithms combined with the widespread availability of smartphones allows diagnostic analysis to be conducted during the patient’s visit to the doctor or at the patient’s home during a telephone conversation. Speech analysis is a simple, low-cost, non-invasive and easy-toprovide method of medical diagnosis. These are remarkable advantages, but there are also disadvantages. The effectiveness of disease diagnoses varies from 65% up to 99%. For that reason it should be treated as a medical screening test and should be an indication of the need for classic medical tests.

13

Comparative Analysis of Classifiers for the Assessment of Respiratory Disorders Using Speech Parameters

75%

Shrivastava P. , Tripathi N. , Singh B. K. , Dewangan B. K.

Archives of Acoustics

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2023

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tom Vol. 48, No. 1

13--24

EN

Non-invasive techniques for the assessment of respiratory disorders have gained increased importance in recent years due to the complexity of conventional methods. In the assessment of respiratory disorders, machine learning may play a very essential role. Respiratory disorders lead to variation in the production of speech as both go hand in hand. Thus, speech analysis can be a useful means for the pre-diagnosis of respiratory disorders. This article aims to develop a machine learning approach to differentiate healthy speech from speech corresponding to different respiratory disorders (affected). Thus, in the present work, a set of 15 relevant and efficient features were extracted from acquired data, and classification was done using different classifiers for healthy and affected speech. To assess the performance of different classifiers, accuracy, specificity (Sp), sensitivity (Se), and area under the receiver operating characteristic curve (AUC) was used by applying both multi-fold cross-validation methods (5-fold and 10-fold) and the holdout method. Out of the studied classifiers, decision tree, support vector machine (SVM), and k-nearest neighbor (KNN) were found more appropriate in providing correct assessment clinically while considering 15 features as well as three significant features (Se > 89%, Sp > 89%, AUC> 82%, and accuracy > 99%). The conclusion was that the proposed classifiers may provide an aid in the simple assessment of respiratory disorders utilising speech parameters with high efficiency. In the future, the proposed approach can be evaluated for the detection of specific respiratory disorders such as asthma, COPD, etc.

14

Isolated word descriptors as control parameters of the computer applications

75%

Porwik P.

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2006

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tom Vol. 10

35--46

EN

This paper is an extended version of the MIT'06 conference contribution. During the conference, many inquiries about the used techniques were performed. Hence, in the paper some parts of investigations were explained and discussed, with greater accuracy. It is shown that the computer applications can be controlled by a human voice. The computer controlling processes are available by means of utterance of isolated words, where application events with the aid of user's voice can be serviced. The voice usage can be convenient for blind or partially sighted users or for persons with limb paresis. The Microsoft application events, by means of the practicable Microsoft Windows firmware MSAA® technology can be analysed. Such technology, together with isolated word descriptors, as voice recognition system, has been presented.

15

Fusing the electromagnetic articulograph, high-speed video cameras and a 16-channel microphone array for speech analysis

75%

Mik Ł. , Lorenc A. , Król D. , Wielgat R. , Święciński R. , Jędryka R.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2018

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tom Vol. 66, nr 3

257--266

EN

Electromagnetic articulography (EMA) is one of the instrumental phonetic research methods used for recording and assessing articulatory movements. Usually, articulographic data are analysed together with standard audio recordings. This paper, however, demonstrates how coupling the articulograph with devices providing other types of information may be used in more advanced speech research. A novel measurement system is presented that consists of the AG 500 electromagnetic articulograph, a 16-channel microphone array with a dedicated audio recorder and a video module consisting of 3 high-speed cameras. It is argued that synchronization of all these devices allows for comparative analyses of results obtained with the three components. To complement the description of the system, the article presents innovative data analysis techniques developed by the authors as well as preliminary results of the system’s accuracy.

16

Narzędzia do analizy mowy – przegląd dostępnych programów i bibliotek

63%

Pieniowska K.

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2019

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tom 13

215-225

EN

This article presents a list of popular speech analysis tools in the form of programs available online to download and in the form of libraries in various programming languages. The first part presents programs used to visualise, to edit, to analyse the speech signal (for example, measurements of the fundamental frequency, intensity or formants) and annotation (segmentation, transcription and labelling of recordings). The second part presents selected libraries available on the GitHub website, which are used for acoustic, phonetic-phonological and prosodic analysis of speech. All tools are described taking into account their functions and capabilities, sources, authors, licenses on which they are made available. The final part of the article presents an evaluation of the described programs taking into account the number and usability of their functions.

PL

Artykuł przedstawia zestawienie popularnych narzędzi do analizy mowy w formie programów dostępnych do pobrania i w formie bibliotek w różnych językach programowania. W pierwszej części zestawione zostały programy służące do wizualizacji sygnału mowy, edytowania, analizy (na przykład pomiarów częstotliwości podstawowej, intensywności czy formantów) oraz anotacji (segmentacji, transkrypcji i etykietowania nagrań). W drugiej części przedstawiono wybrane biblioteki dostępne na stronie GitHub, które służą do akustycznej, fonetyczno-fonologicznej oraz prozodycznej analizy nagrań. Wszystkie narzędzia zostały opisane z uwzględnieniem ich funkcji i możliwości, źródeł, autorów, licencji, na jakich są udostępniane. W ostatnim rozdziale artykułu podjęto próbę ewaluacji opisanych programów, biorąc pod uwagę liczbę i użyteczność ich funkcjonalności.

17

Discrimination between patients with CVDs and healthy people by voiceprint using the MFCC and pitch

63%

Bourouhou A. , Jilbab A. , Cherti M. , Bourouhou Z. , Nacir C.

Diagnostyka

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2021

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tom Vol. 22, No. 4

9--16

EN

Heart diseases cause many deaths around the world every year, and his death rate makes the leader of the killer diseases. But early diagnosis can be helpful to decrease those several deaths and save lives. To ensure good diagnose, people must pass a series of clinical examinations and analyses, which make the diagnostic operation expensive and not accessible for everyone. Speech analysis comes as a strong tool which can resolve the task and give back a new way to discriminate between healthy people and person with cardiovascular diseases. Our latest paper treated this task but using a dysphonia measurement to differentiate between people with cardiovascular disease and the healthy one, and we were able to reach 81.5% in prediction accuracy. This time we choose to change the method to increase the accuracy by extracting the voiceprint using 13 Mel-Frequency Cepstral Coefficients and the pitch, extracted from the people's voices provided from a database which contain 75 subjects (35 has cardiovascular diseases, 40 are healthy), three records of sustained vowels (aaaaa…, ooooo… .. and iiiiiiii….) has been collected from each one. We used the k-near-neighbor classifier to train a model and to classify the test entities. We were able to outperform the previous results, reaching 95.55% of prediction accuracy.

18

Artificial intelligence in medical diagnosis of some brain dysfunctions

51%

Ciota Z. , Napieralski A.

International Journal of Microelectronics and Computer Science

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2015

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tom Vol. 6, nr 1

1--5

EN

The paper presents an analysis of objective evaluation of speech quality. As an example, the recovering process after stroke for patients with vascular lesion of a central nervous system has been taken into account. Application of neural networks gives possibility for objective evaluation of speech quality of patient suffering from disorder of speech motor.

19

Classification of cardiovascular diseases using dysphonia measurement in speech

51%

Bourouhou A. , Jilbab A. , Nacir C. , Hammouch A.

Diagnostyka

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2021

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tom Vol. 22, No. 1

31--37

EN

Cardiovascular disease is the leading cause of death worldwide. The diagnosis is made by non-invasive methods, but it is far from being comfortable, rapid, and accessible to everyone. Speech analysis is an emerging non-invasive diagnostic tool, and a lot of researches have shown that it is efficient in speech recognition and in detecting Parkinson's disease, so can it be effective for differentiating between patients with cardiovascular disease and healthy people? This present work answers the question posed, by collecting a database of 75 people, 35 of whom suffering from cardiovascular diseases, and 40 are healthy. We took from each one three vocal recordings of sustained vowels (aaaaa…, ooooo… .. and iiiiiiii… ..). By measuring dysphonia in speech, we were able to extract 26 features, with which we will train three types of classifiers: the k-near-neighbor, the support vectors machine classifier, and the naive Bayes classifier. The methods were tested for accuracy and stability, and we obtained 81% accuracy as the best result using the k-near-neighbor classifier.

20

L’alcool dans la traduction polonaise de “Verre Cassé” d’Alain Mabanckou

44%

Woch A.

Acta Universitatis Lodziensis. Folia Litteraria Romanica

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2019

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nr 14

159-167

EN

The novel Broken Glass (2005) by a Franco-Congolese writer Alain Mabanckou was translated into Polish by Jacek Giszczak under the title Kielonek in 2008. The plot of the novel is set in a bar, hence the richness and omnipresence of the lexical field related to alcohol. The present article performs a contrastive analysis between the original version and the Polish translation of terms and expressions related to the alcohol universe. The aim is to examinee the translator’s choices, such as the use of literal translation, calque, or tone, as well as to recognise changes and over-translation. As mentioned, the analysis focuses on the translation of terms and expressions related to alcohol, including designating objects (e.g. a ‘glass’ or a ‘bottle’), types of drinks, names that describe drunk persons, words and expressions that suggest a state of alcohol dependence, and verbs and verbal expressions that refer to the action of drinking itself. The article looks into the lexical richness of the French and Polish languages in this particular semantic field, and examines the register of terms used in the source text and the target text.

FR

Le roman Verre Cassé, publié en 2005 par l’écrivain franco-congolais Alain Mabanckou, a été traduit en polonais par Jacek Giszczak sous le titre de Kielonek en 2008. L’action du récit se déroulant dans un bar, le champ lexical de l’alcool y est omniprésent. Pour cette raison, nous nous pencherons sur la traduction des termes et des expressions liés à cet univers, entre autres ceux désignant des objets (comme « verre » ou « bouteille »), des types de boissons, des dénominations relatives à une personne qui s’enivre, des mots et expressions suggérant un état de dépendance et des verbes et des expressions verbales renvoyant à l’action de boire. Nous examinerons les choix du traducteur, tels que le recours à la traduction littérale, au calque, au changement de ton et de registre et à la sur-traduction. Nous réfléchirons à la richesse lexicale du français et du polonais dans ce domaine et nous nous concentrerons sur le registre des termes employés dans le texte de départ et dans le texte d’arrivée.