„b i r d s m o n d” bird sound monitoring database robert wielgat, agnieszka lisowska-lis,...
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„B I R D S M O N D” BIRD SOUND MONITORING DATABASE
Robert Wielgat, Agnieszka Lisowska-Lis, Tomasz Potempa, Daniel KrólDepartment of Technology, State Higher Vocational School in Tarnów,Paweł KoziołComplex of Foothills Landscape Parks in TarnówZbigniew Bonczar, Damian Wiehle, Marcin LisDepartment of Zoology and Ecology, University of Agriculture in KrakówKazimierz Walasz Institute of Environmental Sciences, Jagiellonian University in KrakówAntoni Ligęza, Tomasz Zieliński AGH University of Science and Technology in Kraków
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Reasons for avian monitoring1. Maintenance of biodiversity.
2. Detection of ecological disasters.
3. Monitoring actions in national and
landscape parks
4. Monitoring of environmental quality
(Farmland Bird Index – FBI)
5. Protection of endangered bird species
6. Protection of plants in agriculture
7. Protection of airports and planes
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Problems of avian monitoring actions
• In order to monitor bird species there are organized monitoring programs involving large number of volunteers and skilled experts. • In some actions necessary is catching wild birds (stressful).
• Collecting and analyzing results of observations are often difficult and troublesome. Mistakes are difficult to point out and correct.
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Birdsmond Project ObjectivesThe following task to accomplish are planned in the
years 2008-2011
1. Building recording device capable to record
sounds and ultrasounds from several microphones
and capable to measure GPS position.
2. Building bird attracting device
3. Writing a program for automatic recognition of bird
voices
4. Implementing the data base accessed via Internet
capable to store multimedial data coming from bird
monitoring actions.
5. Evaluating the system during monitoring actions
and scientific expeditions.
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General concept of the monitoring system
Stationary digital recorder
Mobile digital recorder
Bird voice recognizer in unsupervised mode
Information system
Bird voice recognizer in supervised mode
Guest
Expert or Administrator
Observer
Stationary digital recorder
Mobile digital recorder
GPS, movies, photos, weather information
Automatic Observer
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Monitored AreaMonitored Area Includes Małopolska voivodeship in the south-east Poland especially terrain of Complex of Foothills Landscape Parks in the vicinity of Tarnów
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Transects and observation points
In order to experimentally evaluate all the system 6 transect and 7 observation points were chosen in Malopolska region, especially in Complex of Foothills Landscape Parks in Tarnów. Transects and observation points were defined, to represent variety of ecosystems: forests, parks, meadows, ponds, swamp, lakes, river bands, municipal terrains and refuse dump. More than 30 species vocalizations would be analysed during 3 years.
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Transects and observation points
- Observation points
„Krzyskie” ponds
Tarnowiec Radlna
„Stony Town” -
Ciężkowice
Polichty
„Styr” reservation
„Rożnowskie” Lake
Zbylitowska Góra
TarnówPWSZ
Mydlniki
- Transects
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Transect: Tarnowiec-Radlna
Tarnowiec-Radlna transect includes farmland, river banks and small village areas.
Satelite picture of Tarnowiec-Radlna transect
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Transect: „Styr” Reservation
„Styr” Reservation Transect includes mainly forest areas
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Transect: „Stony Town” -Ciężkowice
„Stony Town” Ciężkowice Transect includes forest and small rocks areas
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Transect: „Krzyskie” - Ponds
„Krzyskie” Ponds Transect includes ponds and swamp areas
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Transect: Polichty
Polichty Transect includes mainly forest areas and meadows
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Transect: Rożnowskie Lake
„Rożnowskie” Lake Transect includes artifical lake and forest areas
Satelite picture of Rożnowskie Lake transect
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Observation Point: Zbylitowska Góra
Zbylitowska Góra Observation Point is located on the Dunajec river bank near Collared Sand Martin (lat. Riparia riparia, Ital. topino) colony
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Observation Point: PWSZ Tarnów
PWSZ Tarnów observation point is located in the municipal region
Satelite picture of PWSZ Tarnów observation point
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Observation Point: Mydlniki
Mydlniki observation point is located in the experimental breeding farm of Peregrine Falcon (Lat. Falco peregrinus) (Ital. falco peregrino)
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Conclusion
The general concept of the acoustical avian monitoring system has been presented.
• Preliminary Bird voice recognition experiments involving MFCC and HFCC features as well as DTW classification method have been carried out. Results of the experiments are promising to implement Bird Voice Recognizer.
• 6 transects and 7 observation points have been determined along which initial test observations and recordings have been done.
• Preliminary web site version presenting encyclopaedic information on bird species has been prepared.
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Future work and research
Future research and work in years 2008 - 2011 will include:
• Recognition experiments using TDSC, wavelet, spectral peaks features and HMM classification method.
• Implementation Bird Voice Recognizer as a computer program.
• Hardware implementation of digital recorder and bird attracting device.
• Implementation of data base and web site together with expert system.
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Acknowledgment
Described work is financed from grant of Polish Ministry of Science and Higher Education number N N519 402934.
Lanius collurio – red-backed shrike - L'averla piccola
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THANK YOU VERY MUCH FOR YOUR ATTENTION
For more information visit project website:www.birdsmond.pwsztar.edu.pl
Emberizza citrinella – Yellowhammer - Lo zigolo giallo
Garrulus glandarius – Jay- La ghiandaia
Emberizza citrinella – Yellowhammer - Lo zigolo giallo
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Stationary Digital Recorder
ADC
LCD
MICROCONTROLLER
Keyboard
FAT32Broadbandcondenser
Microphone x 4
MemoryCard
RealTimeClock
DAC
Alluring speakers
MicrophoneAmplifier x 4
Poweramplifier
Return
WirelessTransceiver Antenna
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Mobile Digital Recorder
Return
ADC
MICROCONTROLLERFAT32Broadband
condensermicrophone
x 4
MemoryCard
RealTimeClock
DAC
Headphones
MicrophoneAmplifier x 4
Headphonesamplifier
LCD KeyboardAntenna
GPS
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Bird Voice Recognizer – Unsupervised Mode
Return
• Bird Voice Recognizer is a computer program capable to recognize bird species automatically using formerly recorded voice of the recognized bird species.
• Bird voice recognition is usually performed in the following stages:
• feature extraction• classification
• Bird voice recognition in unsupervised mode can be enhanced by an expert system using additional information like weather forecast, date and hour of the recordings, GPS position which are registered simultaneously with recognized bird voice.
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Feature Extraction
Return
• There are various features which can be extracted from bird voice signal for instance:
TDSC (Time Domain Signal Coding) , spectral peaks, wavelets, MFCC (Mel Frequency Cepstral Coefficients), HFCC (Human Factor Cepstral Coefficients).
• Feature extraction in automatic bird voice recognition is sometimes preceded by initial signal processing like bandpass filtration, noise cancelation etc.
• So far MFCC and HFCC features were tested in the experiments obtainig promising ca. 92% recognition accuracy in the closed set experiment.
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Classification
Return
• The most promising classification methods in bird voice recognition is Dynamic Time Warping (DTW) based word spotting and Hidden Markov Models (HMM) method.
iY
iX
BIRD VOICE X
BIR
D V
OIC
E Y
1 N
1M
DTW
2 3 4 51
o1 o2 o3 o4 o5 o6
a23
a22
b2(o1) b2(o2) b2(o3) b4(o5)b3(o4) b4(o6)
a34 a45a12
a33 a44
HMM
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Bird Voice Recognizer – Supervised Mode
Return
• In the supervised mode bird species recognized by Bird Voice Recognizer can be initially verified by the observer entering data to the system.
• The observer besides synchronized in time automatically captured information like bird voice, weather information, time and date, GPS position can also provide additional information like photos, movies and description of the bird or its behavior.
• Provided information together with initial observer verification can help in further bird species verification by an expert.
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Information system
Information system (IS) will consist of:• Operating system (Linux distribution)• Object-relational database (PostgreSQL);• Data Warehouse supporting OLAP functions,
homogeneously cooperating with database;• Application server;
IS will be bulit in three-tier architecture using MVC (Model – View – Controller) pattern.
In order to store huge amount of multimedia data server will be equipped with almost 10 TB HDDs which are supervised by specialized RAID controller.
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Database
Return
Server with installed relational database will be a storage of data collected as a result of bird species recordings and observation. Database will contain various types of data especially audio files with bird voices, movies, photos, descriptions of particular bird which will be related to each other. Database will be divided into two parts: encyclopaedic one and experimental one.
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Roles – Guest
Return
Guest will have authorization for:• browsing encyclopaedic information
about bird species;• adding bird voices in order to recognize
bird species automatically;
Guest
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Roles – Observer
Return
Observer will have authorization for:• adding results of observations;• modyfing its own observations;• all actions which are covered by guest role;
Observer
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Roles – Expert and Administrator
Return
Expert or AdministratorExpert will have authorization for:
• verifying information provided by observers or an automatic-observer;
• recognition questionable bird voices;• Making statistical analysis supported by data mining • granting role of observer;• all actions which are covered by observers role;
Administrator will have authorization for:• granting role of expert;• all actions which are covered by an expert role;