System which can monitors bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper the electronic devices being integral part of the proposed acoustical bird... more
System which can monitors bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper the electronic devices being integral part of the proposed acoustical bird monitoring system are described. These devices are: digital camera, digital camcorder, multi-channel digital audio recorder, digital alluring device, microphone array, GPS localizator, radio communication module and portable weather station. Some guidelines resulting from authors experience in using described equipment are also given.
Research Interests: Electronic Engineering, Bioacoustics, Electronics, Ecology, Birds (Ecology), and 15 moreGPS, Microprocessor, Microprocessors and Microcontrollers, Cameras, Birdsong, Bird Conservation, Birds, Microphone Arrays, Microprocessors, Digital Cameras, Digital Audio Recording, Birds Monitoring, Bird Population Monitoring, Audio Recording, and Bird Call
The system which can monitor bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper database system together with an expert system and a recognition unit are... more
The system which can monitor bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper database system together with an expert system and a recognition unit are described. Recognition unit (recognizer) recognizes bird species and bird communication signals from the digital signal registered in digital audio recorder. Information about bird species and communication system obtained from recognizer supported by an expert system is stored in the database system. Some initial results of recognition experiments are also given.
Research Interests:
Automatic detection of bird species by their calls is studied in this paper. The conducted research is split into three experiments in which two birds’ species-specific filtration schemes are examined in comparison with experiment... more
Automatic detection of bird species by their calls is studied in this paper. The conducted research is split into three experiments in which two birds’ species-specific filtration schemes are examined in comparison with experiment performed on unfiltered raw data. As a classifier hidden Markov models (HMM) with Gaussian mixture models (GMMs) have been used.
Research Interests: Bioacoustics, Automatic Speech Recognition, Speech Recognition, Filtration, Biodiversity, and 14 moreMFCC, Hidden Markov Models, Birdsong, Birds, Biodiversity Monitoring, GMM Analysis, Bioacoustic, HMMs, Digital Filters, Bird Call, Mel-frequency Cepstral Coefficients, GMM-HMM, MFCC (Mel Frequency Cepstral Coefficient), and Mel Frequency Cepstrum Coefficient(MFCC)
The system which can monitor bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper main aspects of using web mapping services in distributed environment together... more
The system which can monitor bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper main aspects of using web mapping services in distributed environment together with database management system are described. Furthermore, architecture of the subsystem responsible for storing, managing and exchanging geospatial data with web mapping interfaces is proposed. Also some examplary results of querying geospatial information from the Acoustical Bird Monitoring System (ABMS) and external GIS servers are presented. GIS in the acoustical bird monitoring system.
Research Interests:
Acoustical bird monitoring system is a new tool under construction, which will provide automatic support for bird species recognition. The project is an interdisciplinary research which involves specialists from ecology, biology,... more
Acoustical bird monitoring system is a new tool under construction, which will provide automatic support for bird species recognition. The project is an interdisciplinary research which involves specialists from ecology, biology, database, electronics, electro- acoustics as well as experts from nature protection institutions. One of the crucial aspects in the project are bird voices recordings. The paper presents the methods of recordings, compulsory and optional information accompanying the recordings, exemplary species chosen for recordings, tools applied for data analysis. In the years 2008 and 2009 seventy six scientific expeditions dedicated to bird species recordings were undertaken. The collected and acoustically analysed material was about 152 hours of recordings. 49 bird species vocalizations were recorded and analysed.
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Results from preliminary research on recognition of Polish birds’ species are presented in the paper. Bird voices were recorded in a highly noised municipal environment. High 96 kHz sampling frequency has been used. As a feature set... more
Results from preliminary research on recognition of Polish birds’ species are presented in the paper. Bird voices were recorded in a highly noised municipal environment. High 96 kHz sampling frequency has been used. As a feature set standard mel-frequency cepstral coefficients (MFCC) and recently proposed human-factor cepstral coefficients (HFCC) parameters were selected. Superior performance of the HFCC features over MFCC ones has been observed. Proper limiting of the maximal frequency during HFCC feature extraction results in increasing accuracy of birds’ species recognition. Good initial results are very promising for practical application of the methods described in the paper in monitoring of protected birds’ area.
Research Interests: Technology, Bioacoustics, Signal Processing, Human Factors, Dynamic programming, and 16 moreEnvironmental Monitoring, Speech Recognition, MFCC, Microphones, Feature Extraction, Dynamic Time Warping, Bioacoustic, Mel Frequency Cepstral Coefficient, Frequency Modulation, MFCC features, DTW, Species Recognition, Sampling Frequency, Human-Factor Cepstral Coefficients, HFCC, and Bird Species Recognition(Environmental Monitoring, Speech Recognition, MFCC, Microphones, Feature Extraction, Dynamic Time Warping, Bioacoustic, Mel Frequency Cepstral Coefficient, Frequency Modulation, MFCC features, DTW, Species Recognition, Sampling Frequency, Human-Factor Cepstral Coefficients, HFCC, and Bird Species Recognition)
(Environmental Monitoring, Speech Recognition, MFCC, Microphones, Feature Extraction, Dynamic Time Warping, Bioacoustic, Mel Frequency Cepstral Coefficient, Frequency Modulation, MFCC features, DTW, Species Recognition, Sampling Frequency, Human-Factor Cepstral Coefficients, HFCC, and Bird Species Recognition)
Acoustical bird monitoring system is a new tool under construction, which will provide automatic support for bird species recognition. The project is an interdisciplinary research which involves specialists from ecology, biology,... more
Acoustical bird monitoring system is a new tool under construction, which will provide automatic support for bird species recognition. The project is an interdisciplinary research which involves specialists from ecology, biology, database, electronics, electro- acoustics as well as experts from nature protection institutions. One of the crucial aspects in the project are bird voices recordings. The paper presents the methods of recordings, compulsory and optional information accompanying the recordings, exemplary species chosen for recordings, tools applied for data analysis. In the years 2008 and 2009 seventy six scientific expeditions dedicated to bird species recordings were undertaken. The collected and acoustically analysed material was about 152 hours of recordings. 49 bird species vocalizations were recorded and analysed.
Research Interests:
W zagadnieniach dotyczących ochrony środowiska ważnym zagadnieniem jest wykrywanie i monitorowanie obecności określonego gatunku ptaka na danym terytorium, czyli tzw. monitoring ptaków. W celu monitorowania obecności ptaków w ramach... more
W zagadnieniach dotyczących ochrony środowiska ważnym zagadnieniem jest wykrywanie i monitorowanie obecności określonego gatunku ptaka na danym terytorium, czyli tzw. monitoring ptaków. W celu monitorowania obecności ptaków w ramach różnorodnych akcji organizowanych przez parki krajobrazowe oraz inne instytucje są angażowane duże grupy ludzi, od których wymaga się dodatkowo odpowiednich umiejętności. Pociąga to za sobą duże koszty społeczne oraz sprawia wiele trudności organizacyjnych. Rozwiązaniem zaprezentowanego problemu może być system automatycznego monitorowania różnych gatunków ptaków za pomocą metod wykorzystywanych do automatycznego rozpoznawania mowy ludzkiej. Zaprezentowana w pracy koncepcja systemu automatycznego monitoraownia ptaków została oparta na rozpoznawaniu głosów ptaków wykorzystującego metodę klasyfikacji za pomocą nieliniowej transformacji czasowej (ang. DTW) oraz ekstrakcję cech HFCC (Human Factor Cepstral Coefficients) z sygnału dźwiękowego ptaków. Zastosowanie cech HFCC dotychczas nie stosowanych do rozpoznawania głosów ptaków dało bardzo obiecujące wyniki. Osiągnięte skuteczności rozpoznawania pozwalają na zastosowanie prezentowanych w pracy metod w systemach monitoringu ptaków. W artykule podano również pewne zasady dotyczące warunków nagrywania głosów ptaków oraz wstępnego przetwarzania nagranego sygnału mające na celu maksymalizację skuteczności rozpoznawania.
Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to... more
Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to support recognition process, analysed signals have been appropriately filtered before classification in the so called prefiltration process. The prefiltration strategy assumed using n-th order IIR Butterworth filter bank. Each filter from the filter bank was applied for band pass filtration in the bird species-specific and signal type band. Increase of recognition accuracy has been observed in case of prefiltration with properly chosen filter order. Experiments have been carried out on the set of bird voices containing 30 bird species, one of which is endangered with extinction.
Research Interests: Bioacoustics, Digital Signal Processing, Automatic Speech Recognition, Speech Recognition, Signal Analysis, and 21 moreFeature Selection, MFCC, Butterworth Filter Design, Noise, Hidden Markov Models, Birdsong, Birds, Classification, Feature Extraction, Filters, Band Pass Filter, MFCC features, Digital Filters, Bird Call, Classification Algorithms, Signal Classification, Mel-frequency Cepstral Coefficients, Butterworth filters, IIR digital filter, Prefiltration, and Bird Voices(Feature Selection, MFCC, Butterworth Filter Design, Noise, Hidden Markov Models, Birdsong, Birds, Classification, Feature Extraction, Filters, Band Pass Filter, MFCC features, Digital Filters, Bird Call, Classification Algorithms, Signal Classification, Mel-frequency Cepstral Coefficients, Butterworth filters, IIR digital filter, Prefiltration, and Bird Voices)
(Feature Selection, MFCC, Butterworth Filter Design, Noise, Hidden Markov Models, Birdsong, Birds, Classification, Feature Extraction, Filters, Band Pass Filter, MFCC features, Digital Filters, Bird Call, Classification Algorithms, Signal Classification, Mel-frequency Cepstral Coefficients, Butterworth filters, IIR digital filter, Prefiltration, and Bird Voices)
System which can monitors bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper digital audio recorder being integral part of the proposed acoustical bird... more
System which can monitors bird species based on automatic bird voices recognition is very useful in order to protect biodiversity of avifauna. In the paper digital audio recorder being integral part of the proposed acoustical bird monitoring system are described. Recorder has been originally designed by authors and the performance has been tested in series of experiments. Some guidelines resulting from authors experience in using described equipment are also given.
Research Interests: Digital Signal Processing, Ultrasound, Recording, Biodiversity, Enviromental Studies, and 14 moreSound Recording, Microphones, Bird Conservation, Birds, Ultrasonics, Spectrogram, Analog to Digitial Converters, Microphone Arrays, Spectrograph, Bird Call, Analog to Digital Conversion, Sound Recording Technology, Multichannel Audio, and recording equipment
Method for improving audio signals recognition using multimedia database is presented in the paper. Recognition using signals patterns matching was assumed. Large number of signal patterns prolongs recognition time and may decrease... more
Method for improving audio signals recognition using multimedia database is presented in the paper. Recognition using signals patterns matching was assumed. Large number of signal patterns prolongs recognition time and may decrease recognition accuracy. Initial preselection of signal patterns based on chosen signal parameters can alleviate problem. Comparison of effectiveness of preselection method for parameters was examined.
Research Interests: Environmental Science, Bioacoustics, Database Systems, Speaker Recognition, Multimedia, and 15 moreAutomatic Speech Recognition, Speech Recognition, Multimedia Indexing and Searching, Databases, Hidden Markov Models, Bird Conservation, Center of Gravity, Fast Fourier Transform, Signal - to - noise ratio, Bird Call, Signal to Noise Ratio, Normal Distribution, Receiver Operating Characteristic (ROC) analysis, Preselection, and Dynamic Proramming(Automatic Speech Recognition, Speech Recognition, Multimedia Indexing and Searching, Databases, Hidden Markov Models, Bird Conservation, Center of Gravity, Fast Fourier Transform, Signal - to - noise ratio, Bird Call, Signal to Noise Ratio, Normal Distribution, Receiver Operating Characteristic (ROC) analysis, Preselection, and Dynamic Proramming)
(Automatic Speech Recognition, Speech Recognition, Multimedia Indexing and Searching, Databases, Hidden Markov Models, Bird Conservation, Center of Gravity, Fast Fourier Transform, Signal - to - noise ratio, Bird Call, Signal to Noise Ratio, Normal Distribution, Receiver Operating Characteristic (ROC) analysis, Preselection, and Dynamic Proramming)