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Number of results: 77
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Abstract

This article analyses the judgment of the Supreme Court of Poland of 25 June 2020, in which the Court refused to recognise registered mail receipt forms issued by the authorities of the so-called Turkish Republic of Northern Cyprus (TRNC) as foreign official documents, despite the Public Prosecutor General and the claimant arguing to the contrary. The text attempts to show that the ruling is consistent with earlier Polish practice and the majority view in domestic literature. Still, the international jurisprudence shows that there is no clear rule of public international law that would make non-recognition of documents absolutely mandatory in such cases, and some exceptions could even support their recognition under special circumstances. Also, in similar cases foreign national courts do not always refuse recognition.
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Authors and Affiliations

Szymon Zaręba
1
ORCID: ORCID

  1. Assistant Professor, Institute of Law Studies, Polish Academy of Sciences, Warsaw
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Abstract

The present research investigated the effects of short-term musical training on speech recognition in adverse listening conditions in older adults. A total of 30 Kannada-speaking participants with no history of gross otologic, neurologic, or cognitive problems were divided equally into experimental (M = 63 years) and control groups (M = 65 years). Baseline and follow-up assessments for speech in noise (SNR50) and reverberation was carried out for both groups. The participants in the experimental group were subjected to Carnatic classical music training, which lasted for seven days. The Bayesian likelihood estimates revealed no difference in SNR50 and speech recognition scores in reverberation between baseline and followed-up assessment for the control group. Whereas, in the experimental group, the SNR50 reduced, and speech recognition scores improved following musical training, suggesting the positive impact of music training. The improved performance on speech recognition suggests that short-term musical training using Carnatic music can be used as a potential tool to improve speech recognition abilities in adverse listening conditions in older adults.
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Authors and Affiliations

Akhila R. Nandakumar
1
Haralakatta Shivananjappa Somashekara
1
ORCID: ORCID
Vibha Kanagokar
1
ORCID: ORCID
Arivudai Nambi Pitchaimuthu
1
ORCID: ORCID

  1. Department of Audiology and Speech-Language Pathology, Kasturba Medical College, Mangalore Manipal Academy of Higher Education
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Abstract

The main aim of the essay is to examine three philosophical narrations. One of them, Hegel’s master-slave dialectic, clearly inspired the other two, that is: Marx’s reflections in his Economic and Philosophic Manuscripts of 1844 and the interpretation of the Odyssey in Horkheimer and Adorno’s Dialectic of Enlightenment. Whereas Hegel’s dialectic opens a perspective of mutual recognition of individuals, permanently codified in their fundamental rights, the two remaining narrations lead to totally different conclusions. According to young Marx, the subjects not only do not recognize themselves mutually but even, under the influence of economic relationships, treat each other with disregard. Also in Adorno and Horkehimer’s view the labor processes, which according to Hegel led towards the freedom of individuals, distort interpersonal relations and strengthen the growing coercion. At the end, the proposal of Jürgen Habermas is taken into consideration. He argues that communication acts instead of labor processes are the real emancipating factor.

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Authors and Affiliations

Jakub Kloc-Konkołowicz
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Abstract

This study examined whether differences in reverberation time (RT) between typical sound field test rooms used in audiology clinics have an effect on speech recognition in multi-talker environments. Separate groups of participants listened to target speech sentences presented simultaneously with 0-to-3 competing sentences through four spatially-separated loudspeakers in two sound field test rooms having RT = 0:6 sec (Site 1: N = 16) and RT = 0:4 sec (Site 2: N = 12). Speech recognition scores (SRSs) for the Synchronized Sentence Set (S3) test and subjective estimates of perceived task difficulty were recorded. Obtained results indicate that the change in room RT from 0.4 to 0.6 sec did not significantly influence SRSs in quiet or in the presence of one competing sentence. However, this small change in RT affected SRSs when 2 and 3 competing sentences were present, resulting in mean SRSs that were about 8-10% better in the room with RT = 0:4 sec. Perceived task difficulty ratings increased as the complexity of the task increased, with average ratings similar across test sites for each level of sentence competition. These results suggest that site-specific normative data must be collected for sound field rooms if clinicians would like to use two or more directional speech maskers during routine sound field testing.

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Authors and Affiliations

Kim Abouchacra
Janet Koehnke
Joan Besing
Tomasz Letowski
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Abstract

A phoneme segmentation method based on the analysis of discrete wavelet transform spectra is described. The localization of phoneme boundaries is particularly useful in speech recognition. It enables one to use more accurate acoustic models since the length of phonemes provide more information for parametrization. Our method relies on the values of power envelopes and their first derivatives for six frequency subbands. Specific scenarios that are typical for phoneme boundaries are searched for. Discrete times with such events are noted and graded using a distribution-like event function, which represent the change of the energy distribution in the frequency domain. The exact definition of this method is described in the paper. The final decision on localization of boundaries is taken by analysis of the event function. Boundaries are, therefore, extracted using information from all subbands. The method was developed on a small set of Polish hand segmented words and tested on another large corpus containing 16 425 utterances. A recall and precision measure specifically designed to measure the quality of speech segmentation was adapted by using fuzzy sets. From this, results with F-score equal to 72.49% were obtained.

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Authors and Affiliations

Bartosz Ziółko
Mariusz Ziółko
Suresh Manandhar
Richard Wilson
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Abstract

The article reports three experiments conducted to determine whether musicians possess better ability of recognising the sources of natural sounds than non-musicians. The study was inspired by reports which indicate that musical training develops not only musical hearing, but also enhances various non-musical auditory capabilities. Recognition and detection thresholds were measured for recordings of environmental sounds presented in quiet (Experiment 1) and in the background of a noise masker (Experiment 2). The listener’s ability of sound source recognition was inferred from the recognition-detection threshold gap (RDTG) defined as the difference in signal level between the thresholds of sound recognition and sound detection. Contrary to what was expected from reports of enhanced auditory abilities of musicians, the RDTGs were not smaller for musicians than for non-musicians. In Experiment 3, detection thresholds were measured with an adaptive procedure comprising three interleaved stimulus tracks with different sounds. It was found that the threshold elevation caused by stimulus interleaving was similar for musicians and non-musicians. The lack of superiority of musicians over non-musicians in the auditory tasks explored in this study is explained in terms of a listening strategy known as casual listening mode, which is a basis for auditory orientation in the environment.

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Authors and Affiliations

Andrzej Miśkiewicz
Teresa Rościszewska
Jan Żera
Jacek Majer
Barbara Okoń-Makowska
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Abstract

Speech emotion recognition is an important part of human-machine interaction studies. The acoustic analysis method is used for emotion recognition through speech. An emotion does not cause changes on all acoustic parameters. Rather, the acoustic parameters affected by emotion vary depending on the emotion type. In this context, the emotion-based variability of acoustic parameters is still a current field of study. The purpose of this study is to investigate the acoustic parameters that fear affects and the extent of their influence. For this purpose, various acoustic parameters were obtained from speech records containing fear and neutral emotions. The change according to the emotional states of these parameters was analyzed using statistical methods, and the parameters and the degree of influence that the fear emotion affected were determined. According to the results obtained, the majority of acoustic parameters that fear affects vary according to the used data. However, it has been demonstrated that formant frequencies, mel-frequency cepstral coefficients, and jitter parameters can define the fear emotion independent of the data used.
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Authors and Affiliations

Turgut Özseven
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Abstract

Biometric identification systems, i.e. the systems that are able to recognize humans by analyzing their physiological or behavioral characteristics, have gained a lot of interest in recent years. They can be used to raise the security level in certain institutions or can be treated as a convenient replacement for PINs and passwords for regular users. Automatic face recognition is one of the most popular biometric technologies, widely used even by many low-end consumer devices such as netbooks. However, even the most accurate face identification algorithm would be useless if it could be cheated by presenting a photograph of a person instead of the real face. Therefore, the proper liveness measurement is extremely important. In this paper we present a method that differentiates between video sequences showing real persons and their photographs. First we calculate the optical flow of the face region using the Farnebäck algorithm. Then we convert the motion information into images and perform the initial data selection. Finally, we apply the Support Vector Machine to distinguish between real faces and photographs. The experimental results confirm that the proposed approach could be successfully applied in practice.

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Authors and Affiliations

Maciej Smiatacz
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Abstract

The paper presents application of differential electronic nose in the dynamic (on-line) volatile measurement. First we compare the classical nose employing only one sensor array and its extension in the differential form containing two sensor arrays working in differential mode. We show that differential nose performs better at changing environmental conditions, especially the temperature, and well performs in the dynamic mode of operation. We show its application in recognition of different brands of tobacco

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Authors and Affiliations

S. Osowski
K. Siwek
T. Grzywacz
K. Brudzewski
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Abstract

Covid-19 pandemic is severely impacting worldwide. A line of research warned that facial occlusion may impair facial emotion recognition, whilst prior research highlighted the role of Trait Emotional Intelligence in the recognition of non-verbal social stimuli. The sample consisted of 102 emerging adults, aged 18-24 (M = 20.76; SD = 2.10; 84% females, 16% males) and were asked to recognize four different emotions (happiness, fear, anger, and sadness) in fully visible faces and in faces wearing a mask and to complete a questionnaire assessing Trait Emotional Intelligence. Results highlighted that individuals displayed lower accuracy in detecting happiness and fear in covered faces, while also being more inaccurate in reporting correct answers. The results show that subjects provide more correct answers when the photos show people without a mask than when they are wearing it. In addition, participants give more wrong answers when there are subjects wearing masks in the photos than when they are not wearing it. In addition, participants provide more correct answers regarding happiness and sadness when in the photos the subjects are not wearing the mask, compared to when they are wearing it. Implications are discussed.
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Authors and Affiliations

Marco Cannavò
1
ORCID: ORCID
Nadia Barberis
1
ORCID: ORCID
Rosalba Larcan
2
ORCID: ORCID
Francesca Cuzzocrea
1
ORCID: ORCID

  1. Università degli studi Magna Graecia Catanzaro, Italy
  2. Università degli studi di Messina, Messina, Italy
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Abstract

This article focuses on the emotionality of belonging among European Union (EU) citizens in the context of the United Kingdom’s (UK) 2016 referendum and its result in favour of the UK leaving the EU, commonly referred to as Brexit. Drawing from testimonies of EU27 citizens in the UK (mainly mid- to long-term residents) published in a book and on blog and Twitter accounts by the not-for-profit and non-political initiative, the ‘In Limbo Project’, it explores a range of emotions which characterise the affective impact of Brexit and how they underpin two key processes disrupting the sense of belonging of EU citizens: the acquisition of ‘migrantness’ and the non-recognition of the contributions and efforts made to belong. The resulting narratives are characterised by senses of ‘unbelonging’, where processes of social bonding and membership are disrupted and ‘undone’. These processes are characterised by a lack of intersubjective recognition in the private, legal and communal spheres, with ambivalent impacts on EU citizens’ longer-term plans to stay or to leave and wider implications for community relations in a post-Brexit society.

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Authors and Affiliations

Rosa Mas Giralt
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Abstract

Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.

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Authors and Affiliations

Željko Nedeljković
Milana Milošević
Željko Đurović
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Abstract

In this paper a review on biometric person identification has been discussed using features from retinal fundus image. Retina recognition is claimed to be the best person identification method among the biometric recognition systems as the retina is practically impossible to forge. It is found to be most stable, reliable and most secure among all other biometric systems. Retina inherits the property of uniqueness and stability. The features used in the recognition process are either blood vessel features or non-blood vessel features. But the vascular pattern is the most prominent feature utilized by most of the researchers for retina based person identification. Processes involved in this authentication system include pre-processing, feature extraction and feature matching. Bifurcation and crossover points are widely used features among the blood vessel features. Non-blood vessel features include luminance, contrast, and corner points etc. This paper summarizes and compares the different retina based authentication system. Researchers have used publicly available databases such as DRIVE, STARE, VARIA, RIDB, ARIA, AFIO, DRIDB, and SiMES for testing their methods. Various quantitative measures such as accuracy, recognition rate, false rejection rate, false acceptance rate, and equal error rate are used to evaluate the performance of different algorithms. DRIVE database provides 100% recognition for most of the methods. Rest of the database the accuracy of recognition is more than 90%.

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Authors and Affiliations

Poonguzhali Elangovan
Malaya Kumar Nath
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Abstract

The paper considers the problem of increasing the generalization ability of classification systems by creating an ensemble of classifiers based on the CNN architecture. Different structures of the ensemble will be considered and compared. Deep learning fulfills an important role in the developed system. The numerical descriptors created in the last locally connected convolution layer of CNN flattened to the form of a vector, are subjected to a few different selection mechanisms. Each of them chooses the independent set of features, selected according to the applied assessment techniques. Their results are combined with three classifiers: softmax, support vector machine, and random forest of the decision tree. All of them do simultaneously the same classification task. Their results are integrated into the final verdict of the ensemble. Different forms of arrangement of the ensemble are considered and tested on the recognition of facial images. Two different databases are used in experiments. One was composed of 68 classes of greyscale images and the second of 276 classes of color images. The results of experiments have shown high improvement of class recognition resulting from the application of the properly designed ensemble.
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Authors and Affiliations

Robert Szmurło
1
ORCID: ORCID
Stanislaw Osowski
2
ORCID: ORCID

  1. Faculty of Electrical Engineering, Warsaw University of Technology, Koszykowa 75, 00-662 Warszawa, Poland
  2. Faculty of Electronic Engineering, Military University of Technology, gen. S. Kaliskiego 2, 00-908 Warszawa, Poland
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Abstract

The presented results are for the numerical verification of a method devised to identify an unknown spatio-temporal distribution of heat flux that occurs at the surface of a thin aluminum plate, as a result of pulsed laser beam excitation. The presented identification of boundary heat flux function is a part of the newly proposed laser beam profiling method and utilizes artificial neural networks trained on temperature distributions generated with the ANSYS Fluent solver. The paper focuses on the selection of the most effective neural network hyperparameters and compares the results of neural network identification with the Levenberg–Marquardt method used earlier and discussed in previous articles. For the levels of noise measured in physical experiments (0.25–0.5 K), the accuracy of the current parameter estimation method is between 5 and 10%. Design changes that may increase its accuracy are thoroughly discussed.
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Authors and Affiliations

Karol Pietrak
1
ORCID: ORCID
Radosław Muszyński
1
Adam Marek
1
Piotr Łapka
1
ORCID: ORCID

  1. Faculty of Power and Aeronautical Engineering, Warsaw University of Technology, ul. Nowowiejska 24, 00-665 Warsaw, Poland
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Abstract

The paper presents the fusion approach of different feature selection methods in pattern recognition problems. The following methods are examined: nearest component analysis, Fisher discriminant criterion, refiefF method, stepwise fit, Kolmogorov-Smirnov criteria, T2-test, Kruskall-Wallis test, feature correlation with class, and SVM recursive feature elimination. The sensitivity to the noisy data as well as the repeatability of the most important features are studied. Based on this study, the best selection methods are chosen and applied in the process of selection of the most important genes and gene sequences in a dataset of gene expression microarray in prostate and ovarian cancers. The results of their fusion are presented and discussed. The small selected set of such genes can be treated as biomarkers of cancer.
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Bibliography

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Authors and Affiliations

Fabian Gil
1
Stanislaw Osowski
1 2
ORCID: ORCID

  1. Warsaw University of Technology, Pl. Politechniki 1, 00-661 Warsaw, Poland
  2. Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
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Abstract

Courts in Poland, as well as in most countries in the world, allow for the identification of a person on the basis of his/her voice using the so-called voice presentation method, i.e., the auditory method. This method is used in situations where there is no sound recording and the perpetrator of the criminal act was masked and the victim heard only his or her voice. However, psychologists, forensic acousticians, as well as researchers in the field of auditory perception and forensic science more broadly describe many cases in which such testimony resulted in misjudgement. This paper presents the results of an experiment designed to investigate, in a Polish language setting, the extent to which the passage of time impairs the correct identification of a person. The study showed that 31 days after the speaker’s voice was first heard, the correct identification for a female voice was 30% and for a male voice 40%.
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Authors and Affiliations

Stefan Brachmański
1
ORCID: ORCID
Bartosz Hus
1
Piotr Staroniewicz
1
ORCID: ORCID

  1. Faculty of Electronics, Photonics and Microsystems, Department of Acoustics, Multimedia and Signal Processing Wrocław University of Science and Technology
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Abstract

A variety of algorithms allows gesture recognition in video sequences. Alleviating the need for interpreters is of interest to hearing impaired people, since it allows a great degree of self-sufficiency in communicating their intent to the non-sign language speakers without the need for interpreters. State-of-theart in currently used algorithms in this domain is capable of either real-time recognition of sign language in low resolution videos or non-real-time recognition in high-resolution videos. This paper proposes a novel approach to real-time recognition of fingerspelling alphabet letters of American Sign Language (ASL) in ultra-high-resolution (UHD) video sequences. The proposed approach is based on adaptive Laplacian of Gaussian (LoG) filtering with local extrema detection using Features from Accelerated Segment Test (FAST) algorithm classified by a Convolutional Neural Network (CNN). The recognition rate of our algorithm was verified on real-life data.

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Authors and Affiliations

Filip Csóka
Jaroslav Polec
Tibor Csóka
Juraj Kačur
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Abstract

Sorting coal and gangue is important in raw coal production; accurately identifying coal and gangue is a prerequisite for effectively separating coal and gangue. The method of extracting coal and gangue using image grayscale information can effectively identify coal and gangue, but the recognition rate of the sorting process based on image grayscale information needs to substantially higher than that which is needed to meet production requirements. A sorting method of coal and gangue using object surface grayscale-gloss characteristics is proposed to improve the recognition rate of coal and gangue. Using different comparative experiments, bituminous coal from the Huainan area was used as the experimental object. It was found that the number of pixel points corresponding to the highest level grey value of the grayscale moment and illumination component of the coal and gangue images were combined into a total discriminant value and used as input for the best classification of coal and gangue using the GWO-SVM classification model. The recognition rate could reach up to 98.14%. This method sorts coal and gangue by combining surface greyness and glossiness features, optimizes the traditional greyness-based recognition method, improves the recognition rate, makes the model generalizable, enriches the research on coal and gangue recognition, and has theoretical and practical significance in enterprise production operations.
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Authors and Affiliations

Gang Cheng
1
Yifan Wei
1 2
ORCID: ORCID
Jie Chen
1
Zeye Pan
1

  1. School of Mechanical Engineering, Anhui University of Science and Technology, Huainan, China
  2. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines,Anhui University of Science and Technology, Huainan, China
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Abstract

This article explores the role of recognition in State creation. Basing on an analysis of relations between effectiveness and legality in the process of State creation, it claims that recognition is constitutive of statehood as a subject of international law. The research revolves around the following themes: the role of effectiveness criteria and the conditions of recognition set by international law, the existence of “statehood without effectiveness” in cases of limited effectiveness but general recognition, the study of acquisition of statehood as a process and the notion of collective recognition based on the cases of Kosovo and Palestine. The argumentation is also supported by the analysis of de facto entities and aspiring States in international practice. It draws on the distinction between legal non-recognition and political non-recognition as able to shed some light on the complexity of international practice in this area. The article concludes that recognition is a pre-requisite of statehood, an essential criterion that may overcome weak effectiveness in certain legal contexts, though not a lack of independence. Conversely, effectiveness of government authority over population and territory does not lead to statehood in the meaning of international law in the absence of international recognition.
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Authors and Affiliations

François Finck
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Abstract

Perception takes into account the costs and benefits of possible interpretations of incoming sensory data. This should be especially pertinent for threat recognition, where minimising the costs associated with missing a real threat is of primary importance. We tested whether recognition of threats has special characteristics that adapt this process to the task it fulfils. Participants were presented with images of threats and visually matched neutral stimuli, distorted by varying levels of noise. We found threat superiority effect and liberal response bias. Moreover, increasing the level of noise degraded the recognition of the neutral images to higher extent than the threatening images. To summarise, recognising threats is special, in that it is more resistant to noise and decline in stimulus quality, suggesting that threat recognition is a fast ‘all or nothing’ process, in which threat presence is either confirmed or negated.

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Authors and Affiliations

Ewa Magdalena Król
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Abstract

In this paper, a new feature-extraction method is proposed to achieve robustness of speech recognition systems. This method combines the benefits of phase autocorrelation (PAC) with bark wavelet transform. PAC uses the angle to measure correlation instead of the traditional autocorrelation measure, whereas the bark wavelet transform is a special type of wavelet transform that is particularly designed for speech signals. The extracted features from this combined method are called phase autocorrelation bark wavelet transform (PACWT) features. The speech recognition performance of the PACWT features is evaluated and compared to the conventional feature extraction method mel frequency cepstrum coefficients (MFCC) using TI-Digits database under different types of noise and noise levels. This database has been divided into male and female data. The result shows that the word recognition rate using the PACWT features for noisy male data (white noise at 0 dB SNR) is 60%, whereas it is 41.35% for the MFCC features under identical conditions
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Authors and Affiliations

Sayf A. Majeed
Hafizah Husain
Salina A. Samad
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Abstract

Five models and methodology are discussed in this paper for constructing classifiers capable of recognizing in real time the type of fuel injected into a diesel engine cylinder to accuracy acceptable in practical technical applications. Experimental research was carried out on the dynamic engine test facility. The signal of in-cylinder and in-injection line pressure in an internal combustion engine powered by mineral fuel, biodiesel or blends of these two fuel types was evaluated using the vibro-acoustic method. Computational intelligence methods such as classification trees, particle swarm optimization and random forest were applied.

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Authors and Affiliations

Andrzej Bąkowski
Michał Kekez
Leszek Radziszewski
Alžbeta Sapietova

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