„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

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

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.

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.

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

Monitored AreaMonitored Area Includes Małopolska voivodeship in the south-east Poland especially terrain of Complex of Foothills Landscape Parks in the vicinity of Tarnów

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.

Transects and observation points

- Observation points

„Krzyskie” ponds

Tarnowiec Radlna

„Stony Town” -

Ciężkowice

Polichty

„Styr” reservation

„Rożnowskie” Lake

Zbylitowska Góra

TarnówPWSZ

Mydlniki

- Transects

Transect: Tarnowiec-Radlna

Tarnowiec-Radlna transect includes farmland, river banks and small village areas.

Satelite picture of Tarnowiec-Radlna transect

Transect: „Styr” Reservation

„Styr” Reservation Transect includes mainly forest areas

Transect: „Stony Town” -Ciężkowice

„Stony Town” Ciężkowice Transect includes forest and small rocks areas

Transect: „Krzyskie” - Ponds

„Krzyskie” Ponds Transect includes ponds and swamp areas

Transect: Polichty

Polichty Transect includes mainly forest areas and meadows

Transect: Rożnowskie Lake

„Rożnowskie” Lake Transect includes artifical lake and forest areas

Satelite picture of Rożnowskie Lake transect

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

Observation Point: PWSZ Tarnów

PWSZ Tarnów observation point is located in the municipal region

Satelite picture of PWSZ Tarnów observation point

Observation Point: Mydlniki

Mydlniki observation point is located in the experimental breeding farm of Peregrine Falcon (Lat. Falco peregrinus) (Ital. falco peregrino)

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.

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.

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

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

Stationary Digital Recorder

ADC

LCD

MICROCONTROLLER

Keyboard

FAT32Broadbandcondenser

Microphone x 4

MemoryCard

RealTimeClock

DAC

Alluring speakers

MicrophoneAmplifier x 4

Poweramplifier

Return

WirelessTransceiver Antenna

Mobile Digital Recorder

Return

ADC

MICROCONTROLLERFAT32Broadband

condensermicrophone

x 4

MemoryCard

RealTimeClock

DAC

Headphones

MicrophoneAmplifier x 4

Headphonesamplifier

LCD KeyboardAntenna

GPS

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.

Feature Extraction

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• 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.

Classification

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• 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

Bird Voice Recognizer – Supervised Mode

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• 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.

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.

Database

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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.

Roles – Guest

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Guest will have authorization for:• browsing encyclopaedic information

about bird species;• adding bird voices in order to recognize

bird species automatically;

Guest

Roles – Observer

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Observer will have authorization for:• adding results of observations;• modyfing its own observations;• all actions which are covered by guest role;

Observer

Roles – Expert and Administrator

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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;