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(Field of Science)
Ministry points: Help
Year | Points | List |
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Year 2024 | 100 | Ministry scored journals list 2024 |
Year | Points | List |
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2024 | 100 | Ministry scored journals list 2024 |
2023 | 100 | Ministry Scored Journals List |
2022 | 100 | Ministry Scored Journals List 2019-2022 |
2021 | 100 | Ministry Scored Journals List 2019-2022 |
2020 | 100 | Ministry Scored Journals List 2019-2022 |
2019 | 100 | Ministry Scored Journals List 2019-2022 |
2018 | 35 | A |
2017 | 35 | A |
2016 | 25 | A |
2015 | 25 | A |
2014 | 30 | A |
2013 | 35 | A |
2012 | 35 | A |
2011 | 35 | A |
2010 | 32 | A |
Model:
Points CiteScore:
Year | Points |
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Year 2022 | 4.4 |
Year | Points |
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2022 | 4.4 |
2021 | 3.7 |
2020 | 3.3 |
2019 | 3.2 |
2018 | 3.1 |
2017 | 2.9 |
2016 | 3.2 |
2015 | 3.3 |
2014 | 3.4 |
2013 | 3.1 |
2012 | 3.1 |
2011 | 2.7 |
Impact Factor:
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Papers published in journal
Filters
total: 40
Catalog Journals
Year 2023
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Optimizing Medical Personnel Speech Recognition Models Using Speech Synthesis and Reinforcement Learning
PublicationText-to-Speech synthesis (TTS) can be used to generate training data for building Automatic Speech Recognition models (ASR). Access to medical speech data is because it is sensitive data that is difficult to obtain for privacy reasons; TTS can help expand the data set. Speech can be synthesized by mimicking different accents, dialects, and speaking styles that may occur in a medical language. Reinforcement Learning (RL), in the...
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
Year 2022
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Analysis-by-synthesis paradigm evolved into a new concept
PublicationThis work aims at showing how the well-known analysis-by-synthesis paradigm has recently been evolved into a new concept. However, in contrast to the original idea stating that the created sound should not fail to pass the foolproof synthesis test, the recent development is a consequence of the need to create new data. Deep learning models are greedy algorithms requiring a vast amount of data that, in addition, should be correctly...
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Broadening the scope of measurement and analysis of vibrations of an organ pipe employing intensity probe, simulations, and highspeed camera
PublicationThis paper shows an integrated approach to measure, analyze, and model phenomena occurring in an organ pipe driven by pressurized air. The aim of this paper is two-fold, i.e., to measure the pressure signal and the intensity field around the mouth by means of an intensity probe and to visualize and observe the motion of the air jet, which represents the excitation mechanism of the system. This is realized through two techniques,...
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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...
Year 2021
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network
PublicationThe goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant...
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How Machine Learning Contributes to Solve Acoustical Problems
PublicationMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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Introduction to the special issue on machine learning in acoustics
PublicationWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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Selective monitoring of noise emitted by vehicles involved in road traffic
PublicationAn acoustic intensity probe was developed measures the sound intensity in three orthogonal directions, making possible to calculate the azimuth and elevation angles, describing the sound source position. The acoustic sensor is made in the form of a cube with a side of 10 mm, on the inner surfaces of which the digital MEMS microphones are mounted. The algorithm works in two stages. The first stage is based on the analysis of sound...
Year 2020
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Comparing traffic intensity estimates employing passive acoustic radar and microwave Doppler radar sensor
PublicationThe purpose of our applied research project is to develop an autonomous road sign with built-in radar devices of our design. In this paper, we show that it is possible to calibrate the acoustic vector sensor so that it can be used to measure traffic volume and count the vehicles involved in the traffic through the analysis of the noise emitted by them. Signals obtained from a Doppler radar are used as a reference source. Although...
Year 2019
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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...
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Deep learning model for automated assessment of lexical stress of non-native english speakers
Publication -
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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Discovering Rule-Based Learning Systems for the Purpose of Music Analysis
PublicationMusic analysis and processing aims at understanding information retrieved from music (Music Information Retrieval). For the purpose of music data mining, machine learning (ML) methods or statistical approach are employed. Their primary task is recognition of musical instrument sounds, music genre or emotion contained in music, identification of audio, assessment of audio content, etc. In terms of computational approach, music databases...
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Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublicationThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
Year 2018
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A method for testing the wide-sense stationary uncorrelated scattering assumption fulfillment for an underwater acoustic channel
PublicationWide-sense stationary and uncorrelated scattering (WSSUS) assumptions are often applied for the statistical description of wireless communication channels. However, in the case of underwater acoustic channels the WSSUS model is of limited value. The degree of similarity of in-phase and quadrature components of the channel impulse response, measured with the use of bandpass modulated signals, can be used as an indicator of WSSUS...
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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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Counting and tracking vehicles using acoustic vector sensors
PublicationA method is presented for counting vehicles and for determining their movement direction by means of acoustic vector sensor application. The assumptions of the method employing spatial distribution of sound intensity determined with the help of an integrated 3D intensity probe are discussed. The intensity probe developed by the authors was used for the experiments. The mode of operation of the algorithm is presented in conjunction...
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Eulerian motion magnification applied to structural health monitoring of wind turbines
PublicationSeveral types of defects may occur in wind turbines, as physical damage of blades or gearbox malfunction. A wind farm monitoring and damage prediction system is built to observe abnormal vibrations of elements of wind turbine: blades, nacelle, and tower. Contactless methods are developed which do not require turbine stopping. In this work, structural health monitoring of a wind turbine is evaluated using a conversion from the captured...
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