Search
Search results for: mel frequency cepstral coefficients
-
Automatic labeling of traffic sound recordings using autoencoder-derived features
PublicationAn approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...
-
Audio Feature Analysis for Precise Vocalic Segments Classification in English
PublicationAn approach to identifying the most meaningful Mel-Frequency Cepstral Coefficients representing selected allophones and vocalic segments for their classification is presented in the paper. For this purpose, experiments were carried out using algorithms such as Principal Component Analysis, Feature Importance, and Recursive Parameter Elimination. The data used were recordings made within the ALOFON corpus containing audio signal...
-
Remote Health Monitoring of Wind Turbines Employing Vibroacoustic Transducers and Autoencoders
PublicationImplementation of remote monitoring technology for real wind turbine structures designed to detect potential sources of failure is described. An innovative multi-axis contactless acoustic sensor measuring acoustic intensity as well as previously known accelerometers were used for this purpose. Signal processing methods were proposed, including feature extraction and data analysis. Two strategies were examined: Mel Frequency Cepstral...
-
Examining Influence of Distance to Microphone on Accuracy of Speech Recognition
PublicationThe problem of controlling a machine by the distant-talking speaker without a necessity of handheld or body-worn equipment usage is considered. A laboratory setup is introduced for examination of performance of the developed automatic speech recognition system fed by direct and by distant speech acquired by microphones placed at three different distances from the speaker (0.5 m to 1.5 m). For feature extraction from the voice signal...
-
Ranking Speech Features for Their Usage in Singing Emotion Classification
PublicationThis paper aims to retrieve speech descriptors that may be useful for the classification of emotions in singing. For this purpose, Mel Frequency Cepstral Coefficients (MFCC) and selected Low-Level MPEG 7 descriptors were calculated based on the RAVDESS dataset. The database contains recordings of emotional speech and singing of professional actors presenting six different emotions. Employing the algorithm of Feature Selection based...
-
Buzz-based recognition of the honeybee colony circadian rhythm
PublicationHoneybees are one of the highly valued pollinators. Their work as individuals is appreciated for crops pollination and honey production. It is believed that work of an entire bee colony is intense and almost continuous. The goal of the work presented in this paper is identification of bees circadian rhythm with a use of sound-based analysis. In our research as a source of information on bee colony we use their buzz that have been...
-
EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublicationThe problem of video framerate and audio/video synchronization in audio-visual speech recognition is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
-
EXAMINING INFLUENCE OF VIDEO FRAMERATE AND AUDIO/VIDEO SYNCHRONIZATION ON AUDIO-VISUAL SPEECH RECOGNITION ACCURACY
PublicationThe problem of video framerate and audio/video synchronization in audio-visual speech recogni-tion is considered. The visual features are added to the acoustic parameters in order to improve the accuracy of speech recognition in noisy conditions. The Mel-Frequency Cepstral Coefficients are used on the acoustic side whereas Active Appearance Model features are extracted from the image. The feature fusion approach is employed. The...
-
Application of autoencoder to traffic noise analysis
PublicationThe aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...
-
Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
-
SYNAT_MUSIC_GENRE_FV_173
Open Research DataThis is the original dataset containing 51582 music tracks (22 music genres) and 173 element-feature vector [1-6,9]. A collection of more than 50000 music excerpts described with a set of descriptors obtained through the analysis of 30-second mp3 recordings was gathered in a database called SYNAT. The SYNAT database was realized by the Gdansk University...
-
SYNAT Music Genre Parameters PCA 19
Open Research DataThe dataset contains feature vector after Principal Component Analysis (PCA) performing, so there are 11 music genres and 19-element vector derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of 52532 music excerpts described...
-
SYNAT_PCA_48
Open Research DataThere is a series of datasets containing feature vectors derived from music tracks. The dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 48-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier...
-
SYNAT_PCA_11
Open Research DataThe dataset contains 51582 music tracks (22 music genres) and feature vector after Principal Component Analysis (PCA) performing, so there are 11-element vectors derived from music excerpts. Originally, a feature vector containing 173 elements was conceived in earlier research studies carried out by the team of authors [1-6]. A collection of more than...
-
Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
-
Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...
-
Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is common for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected as...
-
Automatic Breath Analysis System Using Convolutional Neural Networks
PublicationDiseases related to the human respiratory system have always been a burden for the entire society. The situation has become particularly difficult now after the outbreak of the COVID-19 pandemic. Even now, however, it is not uncommon for people to consult their doctor too late, after the disease has developed. To protect patients from severe disease, it is recommended that any symptoms disturbing the respiratory system be detected...
-
Decoding of the FSK signal with noise and distortion with the use of coefficients of the time-frequency transform.
PublicationStreszczenie: Przeanalizowano sygnał z modulacją FSK wykorzystując metodę transformacji czasowo-częstotliwościowej różniące się sposobem podziału płaszczyzny TF na atomy: krótko-okresowej transformacji Fouriera, transformacji falkowej i transformacji pakietami falkowymi. Transformacja falkowa zapewnia dobrą lokalizację czasową zakłóceń o wielkiej częstotliwości, podczas gdy transformacja pakietami falkowymi zapewnia dobrą lokalizację...
-
Karolina Lademann mgr
PeopleCurriculum vitae
-
Karolina Lademann Mgr
People -
Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
-
Multistage generalized adaptive notch filter with improved accuracy
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of the coefficient estimates. The paper proposes a novel multistage GANF with accuracy improved in this aspect. The processing pipeline consists of three stages. The preliminary...
-
Temperature influence on tyre/road noise frequency spectra
PublicationThe correction for temperature effect on measured tyre/road noise is very important as it may be one of the main sources of errors in measurement results due to substantial influence of this parameter on obtained values. The latest version of the Technical Specification ISO/CD TS 13471-1 about Temperature Corrections contains a proposal of correction procedure for normalizing measured noise levels to a reference air temperature...
-
Estimation of structural stiffness with the use of Particle Swarm Optimization
PublicationThe paper presents the theoretical background and four applications examples of the new method for the estimation of support stiffness coefficients of complex structures modelled discretely (e.g. with the use of the Finite Element Model (FEM) method based on the modified Particle Swarm Optimization (PSO) algorithm. In real-life cases, exact values of the supports’ stiffness coefficients may change for various reasons...
-
SPECTRAL-BASED MODAL PARAMETERS IDENTIFICATION WITH MULTIPLE PARTICLE SWARMS OPTIMIZATION
PublicationThe paper presents usage of a Particle Swarm Optimization [1] based algorithm for spectral-based modal parameters identification. The main algorithm consists of two groups of swarms, namely, scouts and helpers. For the first group additional penalizing process is provided to force separation of scouting swarms in frequency space. The swarms have an ability to communicate with each other. At first stage, each swarm focuses on a...
-
A self-optimization mechanism for generalized adaptive notch smoother
PublicationTracking of nonstationary narrowband signals is often accomplished using algorithms called adaptive notch filters (ANFs). Generalized adaptive notch smoothers (GANSs) extend the concepts of adaptive notch filtering in two directions. Firstly, they are designed to estimate coefficients of nonstationary quasi-periodic systems, rather than signals. Secondly, they employ noncausal processing, which greatly improves their accuracy and...
-
Metamaterial-Based Sub-Microwave Electromagnetic Field Energy Harvesting System
PublicationThis paper presents the comprehensive analysis of the sub-microwave, radio frequency band resonant metastructures’ electromagnetic properties with a particular emphasis on the possibility of their application in energy harvesting systems. Selected structures based on representative topologies of metamaterials have been implemented in the simulation environment. The models have been analyzed and their substitute average electromagnetic...
-
ESTYMACJA WSPÓŁCZYNNIKÓW SZTYWNOŚCI ZAMOCOWANIA PODATNEGO PRZEDMIOTU OBRABIANEGO NA STOLE FREZARKI
PublicationW pracy przedstawiono metodę estymacji współczynników sztywności Elementów Sprężystych (ES) modelujących zamocowanie podatnego wielkogabarytowego przedmiotu obrabianego na stole frezarki. Proponowana metoda bazuje na algorytmie optymizacji za pomocą roju cząstek (ang. Particle Swarm Optimization), który pozwala na uzyskanie dobrej zgodności (aktualizacji) modelu Metody Elementów Skończonych (MES) z modelem pochodzącym z identyfikacji...
-
Optimization of clamping stiffness during milling of high-dimensional structures with the use of techniques of experiment – aided virtual prototyping
PublicationThe subject of this paper is a method of searching for conditions of minimizing the vibration level of a tool-high dimensional flexible workpiece, at unchangeable technological parameters of the machining process. It depends on repeatable change of the values of the stiffness coefficients as soon as an optimal vibration state of the workpiece approaches. There are assessed the values of dominant ”peaks” in the frequency spectra...
-
Novel Interpolation Method of Multi-DFT-Bins for Frequency Estimation of Signal with Parameter Step Change
PublicationThe IpDFT(Interpolation Discrete Fourier Trans-form) method is one of the most commonly used non-parametric methods. However, when a parameter (frequency, amplitude or phase) step changes in the DFT period, the DFT coefficients will be distorted seriously, resulting in the large estimation error of the IpDFT method. Hence, it is a key challenge to find an IpDFT method, which not only can eliminate the effect of the step-changed...
-
Adaptive system for recognition of sounds indicating threats to security of people and property employing parallel processing of audio data streams
PublicationA system for recognition of threatening acoustic events employing parallel processing on a supercomputing cluster is featured. The methods for detection, parameterization and classication of acoustic events are introduced. The recognition engine is based onthreshold-based detection with adaptive threshold and Support Vector Machine classifcation. Spectral, temporal and mel-frequency descriptors are used as signal features. The...
-
A Simplistic Downlink Channel Estimation Method for NB-IoT
PublicationThis paper presents a downlink channel estimation method intended for a Narrowband Internet of Things (NB-IoT) access link. Due to its low computational complexity, this method is well suited for energy-efficient IoT devices, still providing acceptable reception quality in terms of signal-to-noise (SNR) performance. This paper describes the physical layer of NB-IoT within the scope of channel estimation, and also reviews existing...
-
Coplanar Waveguide Fed Ultra-Wideband Antenna Over the Planar and Cylindrical Surfaces
PublicationThe investigation of coplanar waveguide fed ultra-wideband antenna and the influence of the proximity of different materials on the reflection coefficients and radiation character-istics is presented. The antenna is composed of two circular coplanar strips which enclose slot aperture of similar shape and is designed on a thin and flexible substrate. From the modeling and experimental tests the antenna shows good performance in...
-
A Novel Synthesis Technique for Microwave Bandpass Filters with Frequency-Dependent Couplings
PublicationThis paper presents a novel synthesis technique for microwave bandpass filters with frequency-dependent couplings. The proposed method is based on the systematic extraction of a dispersive coupling coefficient using an optimization technique based on the zeros and poles of scattering parameters representing two coupled resonators.The application of this method of synthesis is illustrated using two examples involving four and five-pole...
-
Variable Ratio Sample Rate Conversion Based on Fractional Delay Filter
PublicationIn this paper a sample rate conversion algorithm which allows for continuously changing resampling ratio has been presented. The proposed implementation is based on a variable fractional delay filter which is implemented by means of a Farrow structure. Coefficients of this structure are computed on the basis of fractional delay filters which are designed using the offset window method. The proposed approach allows us to freely...
-
FINITE GROUND CPW-FED UWB ANTENNA OVER THE METALLIC CYLINDRICAL SURFACES
PublicationThe investigation of finite ground coplanar fed ultra-wideband (UWB) antenna and the influence of its curvature and the proximity of circular metallic screen on the reflection coefficients and radiation characteristics is presented. The antenna is composed of two circular coplanar strips which enclose slot aperture of similar shape and is designed on a thin and flexible substrate which allows its bending. The antenna configuration...
-
Analysis and evaluation of grouping methods for effective cutting tool operation
PublicationThis article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving...
-
Rapid Design Tuning of Miniaturized Rat-Race Couplers Using Regression-Based Equivalent Network Surrogates
PublicationA simple technique for fast design tuning of compact rat-race couplers is presented. Our approach involves equivalent circuit representation, corrected by nonlinear functions of frequency with coefficients extracted through nonlinear regression. At the same time, the tuning process connects two levels of coupler representation: EM simulation of the entire circuit and re-optimization of the coupler building blocks (slow-wave cells...
-
Analysis of Lombard speech using parameterization and the objective quality indicators in noise conditions
PublicationThe aim of the work is to analyze Lombard speech effect in recordings and then modify the speech signal in order to obtain an increase in the improvement of objective speech quality indicators after mixing the useful signal with noise or with an interfering signal. The modifications made to the signal are based on the characteristics of the Lombard speech, and in particular on the effect of increasing the fundamental frequency...
-
Generalized adaptive notch smoothers for real-valued signals and systems
PublicationSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
-
Fading Modeling in Maritime Container Terminal Environments
PublicationIn this paper, an analytical model for slow and fast fading effects in maritime container terminals is derived, from fitting distributions to the results of measurements performed in an actual operational environment. The proposed model is composed of a set of equations, enabling to evaluate fading statistical distribution parameters for different system and environments conditions, as a function of frequency, base station antenna...
-
A Wideband Channel Model for Body Area Networks in Circular Metallic Indoor Environments
PublicationIn this paper, the wideband characterization of the propagation channel in circular metallic indoor environments is addressed, regarding Body Area Networks and 5G small cells, an analytical model for the dependence of the mean delay and the average delay spread on the circle radius, the working frequency and the distance between the transmitter and the receiver being proposed. The derivation of the model is initially done analytically,...
-
Determination of Peak Impact Force for Buildings Exposed to Structural Pounding during Earthquakes
PublicationStructural pounding between adjacent, insufficiently separated buildings, or bridge segments, has been repeatedly observed during seismic excitations. Such earthquake-induced collisions may cause severe structural damage or even lead to the collapse of colliding structures. The aim of the present paper was to show the results of the study focused on determination of peak impact forces during collisions between buildings exposed...
-
Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublicationW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
-
Investing in wine, precious metals and G-7 stock markets – A co-occurrence analysis for price bubbles
PublicationThis paper used the GSADF test to determine the periods defined in this paper as price bubbles in the three markets studied, i.e. the investment wine market, precious metal market and national stock market indices of G-7 countries. The results obtained enabled the calculation of the values of the phi correlation coefficients, which served the research objective of assessing the co-occurrence of price bubbles in the markets analysed....
-
Stability Analysis of Shunt Active Power Filter with Predictive Closed-Loop Control of Supply Current
PublicationThis paper presents a shunt active power filter connected to the grid via an LCL coupling circuit with implemented closed‐loop control. The proposed control system allows selective harmonic currents compensation up to the 50th harmonic with the utilization of a model‐based predictive current controller. As the system is fully predictive, it provides high effectiveness of the harmonic reduction, which is proved by waveforms achieved...
-
Assessment of dynamic characteristics of thin cylindrical sandwich panels with magnetorheological core
PublicationBased on the equivalent single-layer linear theory for laminated shells, free and forced vibrations of thin cylindrical sandwich panels with magnetorheological core are studied. Five variants of available magnetorheological elastomers differing in their composition and physical properties are considered for smart viscoelastic core. Coupled differential equations in terms of displacements based on the generalized kinematic hypotheses...
-
Nonlocal Vibration of Carbon/Boron-Nitride Nano-hetero-structure in Thermal and Magnetic Fields by means of Nonlinear Finite Element Method
PublicationHybrid nanotubes composed of carbon and boron-nitride nanotubes have manifested as innovative building blocks to exploit the exceptional features of both structures simultaneously. On the other hand, by mixing with other types of materials, the fabrication of relatively large nanotubes would be feasible in the case of macroscale applications. In the current article, a nonlinear finite element formulation is employed to deal with...
-
Ultrasound-Assisted Solvent Extraction of a Porous Membrane Packed Sample for the Determination of Tobacco-Specific Nitrosamines in the Replacement Liquids for E-Cigarettes
PublicationThe content of tobacco-specific nitrosamines (TSNAs) possessing carcinogenic properties has been an important area of research since replacement liquids were introduced for e-cigarettes. A method for determining N′-nitrosonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), N′-nitrosoanatabine (NAT), and N′-nitrosoanabasine (NAB) in replacement liquids for electronic cigarettes was developed using liquid chromatography–tandem...