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Search results for: RECONSTRUCTION OF SPEECH SIGNALS
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Log signals simulation.
PublicationSymulatory logów (urządzeń mierzących prędkość w nawigacji morskiej), które używane są do testowania oraz szkolenia operatorów radarów i systemów antykolizyjnych, powinny posiadać również wyjście impulsowe, które w logu rzeczywistym pochodzi z licznika przebytej drogi, w postaci zadanej liczby impulsów na milę morską. Urządzenie takie to przetwornik cyfrowo-częstotliwościowy w formie programowanego cyfrowo dzielnika częstotliwości....
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Comparison of perforator location in dynamic and static thermographic imaging with Doppler ultrasound in breast reconstruction surgery
PublicationThis paper co mpares the effectiveness of the dTnorm and t90_10 parametrizations in dynamic thermography for imaging location of perforators in TRAM flaps in the intraoperative period. The results were compared with the location detected in a Doppler ultrasound examination. Cold and heat stimulation was used in dynamic thermography. Additionally, these results were compared with static...
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Radio reception signals II 2023/2024
e-Learning CoursesKurs będzie narzędziem pomocniczym przy realizacji laboratorium z tego przedmiotu.
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Database of speech and facial expressions recorded with optimized face motion capture settings
PublicationThe broad objective of the present research is the analysis of spoken English employing a multiplicity of modalities. An important stage of this process, discussed in the paper, is creating a database of speech accompanied with facial expressions. Recordings of speakers were made using an advanced system for capturing facial muscle motion. A brief historical outline, current applications, limitations and the ways of capturing face...
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Stress Detection of Children With ASD Using Physiological Signals
PublicationThis paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot inter- vention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect...
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Detection of dialogue in movie soundtrack for speech intelligibility enhancement
PublicationA method for detecting dialogue in 5.1 movie soundtrack based on interchannel spectral disparity is presented. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity with left and right channels, are detected as dialogue. Subsequently, the dialogue frequency components are boosted to achieve increased dialogue intelligibility....
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Estimation of the short-term predictor parameters of speech under noisy conditions
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublicationThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Estimation of the excitation variances of speech and noise AR-models for enhanced speech coding
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Artur Gańcza dr inż.
PeopleI received the M.Sc. degree from the Gdańsk University of Technology (GUT), Gdańsk, Poland, in 2019. I am currently a Ph.D. student at GUT, with the Department of Automatic Control, Faculty of Electronics, Telecommunications and Informatics. My professional interests include speech recognition, system identification, adaptive signal processing and linear algebra.
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Using concentrated spectrogram for analysis of audio acoustic signals
PublicationThe paper presents results of time-frequency analysis of audio acoustic signals using the method of Concentrated Spectrograph also known as ''Cross-spectral method'' or ''Reassignment method''. Presented algorithm involves signal's local group delay and channelized instantaneous frequency to relevantly redistribute all Short-time Fourier transform lines in time-frequency plain. The main intention of the paper is to compare various...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Bimodal classification of English allophones employing acoustic speech signal and facial motion capture
PublicationA method for automatic transcription of English speech into International Phonetic Alphabet (IPA) system is developed and studied. The principal objective of the study is to evaluate to what extent the visual data related to lip reading can enhance recognition accuracy of the transcription of English consonantal and vocalic allophones. To this end, motion capture markers were placed on the faces of seven speakers to obtain lip...
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Computer vision techniques applied for reconstruction of seafloor 3D images from side scan and synthetic aperture sonars data
PublicationThe Side Scan Sonar and Synthetic Aperture Sonar are well known echo signal processing technologies that produce 2D images of the seafloor. Both systems combines a number of acoustic pings to form a high resolution image of seafloor. It was shown in numerous papers that 2D images acquired by such systems can be transformed into 3D models of seafloor surface by algorithmic approach using intensity information, contained in a grayscaled...
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Method for Clustering of Brain Activity Data Derived from EEG Signals
PublicationA method for assessing separability of EEG signals associated with three classes of brain activity is proposed. The EEG signals are acquired from 23 subjects, gathered from a headset consisting of 14 electrodes. Data are processed by applying Discrete Wavelet Transform (DWT) for the signal analysis and an autoencoder neural network for the brain activity separation. Processing involves 74 wavelets from 3 DWT families: Coiflets,...
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Chirp-rate estimation of FM signals in the time-frequency domain
PublicationNovel dynamic representations of a complex signal in the time-frequency domain including: a channelized instantaneous complex frequency (CICF), a complex local group delay (CLGD) and a channelized instantaneous chirp-rate (CICR) are introduced. The proposed approach is based on the use of the gradient of the short-time Fourier transform complex phase. An interpretation of the newly-introduced distributions especially of the CICR...
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Parametric impulsive noise detector for corrupted audio signals based on hidden Markow model
PublicationThe paper addresses the problem of impulsive noise detection for audio signals. A structure of threshold parameter detectors using modelingof signals was introduced. the algorithm of the noise detection, based on discrete-time hidden Markow model (HMM)of whitened audio signal is elaborated
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Suppression of distortions in signals received from Doppler sensor for vehicle speed measurement
PublicationDoppler sensors are commonly used for movement detection and speed measurement. However, electromagnetic interference and imperfections in sensor construction result in degradation of the signal to noise ratio. As a result, detection of signals reflected from moving objects becomes problematic. The paper proposes an algorithm for reduction of distortions and noise in the signal received from a simple, dual-channel type of a Doppler...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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New perspective on the in vivo use of cold stress dynamic thermography in integumental reconstruction with the use of skin-muscle flaps
PublicationAmong the problems encountered by plastic surgeons is the reconstruction of defects following tumors. One of the reconstructive options is TRAM flap. Despite that anatomy is well-explored, marginal flap necrosis may develop. To minimize complications imaging examinations was designed to determine the degree of flap perfusion. One of them is the thermographic examination.
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Improving the Accuracy of Automatic Reconstruction of 3D Complex Buildings Models from Airborne Lidar Point Clouds
PublicationDue to high requirements of variety of 3D spatial data applications with respect to data amount and quality, automatized, effcient and reliable data acquisition and preprocessing methods are needed. The use of photogrammetry techniques—as well as the light detection and ranging (LiDAR) automatic scanners—are among attractive solutions. However, measurement data are in the form of unorganized point clouds, usually requiring transformation...
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublicationIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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Diagnosing wind turbine condition employing a neural network to the analysis of vibroacoustic signals
PublicationIt is important from the economic point of view to detect damage early in the wind turbines before failures occur. For this purpose, a monitoring device was built that analyzes both acoustic signals acquired from the built-in non-contact acoustic intensity probe, as well as from the accelerometers, mounted on the internal devices in the nacelle. The signals collected in this way are used for long-term training of the autoencoder...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublicationA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Intelligent processing of stuttered speech.
PublicationW artykule zaprezentowano kilka metod analizy i automatycznego zliczania potknięć artykulacyjnych, związanych z jąkaniem się, opartych na wykorzystaniu algorytmów uczących się sztucznych sieci neuronowych i zbiorów przybliżonych.
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Quality Evaluation of Speech Transmission via Two-way BPL-PLC Voice Communication System in an Underground Mine
PublicationIn order to design a stable and reliable voice communication system, it is essential to know how many resources are necessary for conveying quality content. These parameters may include objective quality of service (QoS) metrics, such as: available bandwidth, bit error rate (BER), delay, latency as well as subjective quality of experience (QoE) related to user expectations. QoE is expressed as clarity of speech and the ability...
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Simulation of incremental encoder signals
PublicationPrzedstawiono generator sygnału impulsowego do symulacji sygnału z przetwornika obrotowo-impulsowego w stanach przejściowych. Omówiono algorytmy wyznaczenia przedziałów międzyimpulsowych dla trzech rodzajów zmian prędkości obrotowej: liniowej, wykładniczej oraz sinusoidalnej. Przeanalizowano błędy kwantowania wynikające z cyfrowej realizacji generatora.
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Signals features extraction in radioisotope liquid-gas flow measurements using wavelet analysis
PublicationKnowledge of the structure of a flow is significant for the proper conduct of a number of industrial processes. In this case, a description of a two-phase flow regimes is possible by use of the time-series analysis in time, frequency and state-space domain. In this article the Discrete Wavelet Transform (DWT) is applied for analysis of signals obtained for water-air flow using gamma ray absorption. The presented method was illustrated...
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Analysis of the Ways to Identify Rail Running Surface Defects by Means of Vibration Signals
PublicationTh e article discusses a preliminary concept of a method enabling the identifi cation of chosen rail running surface defects, such as squats, spalling, and running surface defects, by analysing the parameters of vibration signals. It features a description of the methodology of the conducted tests, the scope thereof, and the selection of the measurement points with specifi c defect types. Th e article covers selected results of...
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Plasma models, contribution matrix for detector setup and generated projections for plasma emissivity reconstruction in fusion devices
Open Research DataThe original plasma models for fusion devices, together with the complementary detector setup in the form of a contribution matrix and generated projections. Samples are packed inside a Plasma Tomography Format (PTF) files which is a part of the Plasma Tomography in Fusion Devices Python package, and inside the general JSON format. The constructed dataset...
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Time reconstruction and performance of the CMS electromagnetic calorimeter
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Reconstruction of input signal of sensor with frequency output
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An EIT reconstruction algorithm based on noisy data.
PublicationPraca przedstawia algorytm rekonstrukcji oparty o zmodyfikowany algorytm Gaussa - Newtona. Algorytm uwzględnia istnienie elektrod pomiarowych w tomografii elektroimpedancyjnej. Elektrody charakteryzują się rozmiarem i impedancją. Dodatkowo algorytm zakłada istnienie szumu w sygnale mierzonym. Zostało pokazane, że dobór optymalnego wzorca pobudzenia znacząco poprawia odporność algorytmu rekonstrukcyjnego na szum w danych. Dwie...
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Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances
PublicationArchive audio files are often corrupted by impulsive disturbances, such as clicks, pops and record scratches. This paper presents a new method for elimination of impulsive disturbances from stereo audio signals. The proposed approach is based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other one taking care of long-term correlations. The method...
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Comparison of Language Models Trained on Written Texts and Speech Transcripts in the Context of Automatic Speech Recognition
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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublicationThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...
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Methods for quality improvement of multibeam and LiDAR point cloud data in the context of 3D surface reconstruction
PublicationPoint cloud dataset is the transitional data model used in several marine and land remote-sensing applications. During further steps of processing, the transformation of point cloud spatial data to more complex models containing higher order geometric structures like edges and facets may be possible, if an appropriate quality level of input data is provided. Point cloud datasets usually contain a considerable amount of undesirable...
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New First - Path Detector for LTE Positioning Reference Signals
PublicationIn today's world, where positioning applications reached a huge popularity and became virtually ubiquitous, there is a strong need for determining a device location as accurately as possible. A particularly important role in positioning play cellular networks, such as Long Term Evolution (LTE). In the LTE Observed Time Difference of Arrival (OTDOA) positioning method, precision of device location estimation depends on accuracy...
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Direct modulation for conventional matrix converters using analytical signals and barycentric coordinates
PublicationThis paper proposes the generalized direct modulation for Conventional Matrix Converters (CMC) using the concept of analytical signals and barycentric coordinates. The paper proposes a novel approach to the Pulse Width Modulation (PWM) duty cycle computing, which allows faster prototyping of direct control algorithms. The explanation of the new idea using analytical considerations demonstrating the principles of direct voltage...
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Propagation of initially sawtooth periodic and impulsive signals in a quasi-isentropic magnetic gas
PublicationThe characteristics of propagation of sawtooth periodic and impulsive signals at a transducer are analytically studied in this work. A plasma under consideration is motionless and uniform at equilibrium, and its perturbations are described by a system of ideal magnetohydrodynamic equations. Some generic heating/cooling function, which in turn depends on equilibrium thermodynamic parameters, may destroy adiabaticity of a flow and...
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Cross-Lingual Knowledge Distillation via Flow-Based Voice Conversion for Robust Polyglot Text-to-Speech
PublicationIn this work, we introduce a framework for cross-lingual speech synthesis, which involves an upstream Voice Conversion (VC) model and a downstream Text-To-Speech (TTS) model. The proposed framework consists of 4 stages. In the first two stages, we use a VC model to convert utterances in the target locale to the voice of the target speaker. In the third stage, the converted data is combined with the linguistic features and durations...
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Investigations of the Methods of Time Delay Measurement of Stochastic Signals Using Cross-correlation with the Hilbert Transform
PublicationThe article presents the results of simulation studies of four methods of estimating time delay for random signals using cross-correlation with the Hilbert Transform. Selected models of mutually delayed stochastic signals were used in the simulations, corresponding to the signals obtained from scintillation detectors in radioisotope measurements of liquid-gas two-phase flow. Standard deviations of the values of the individual functions...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Analysis of Vibration and Acoustic Signals for Noncontact Measurement of Engine Rotation Speed
PublicationThe non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After...
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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Real and imaginary motion classification based on rough set analysis of EEG signals for multimedia applications
PublicationRough set-based approach to the classification of EEG signals of real and imaginary motion is presented. The pre-processing and signal parametrization procedures are described, the rough set theory is briefly introduced, and several classification scenarios and parameters selection methods are proposed. Classification results are provided and discussed with their potential utilization for multimedia applications controlled by the...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...