Presentation on theme: "„B I R D S M O N D” BIRD SOUND MONITORING DATABASE Robert Wielgat, Agnieszka Lisowska-Lis, Tomasz Potempa, Daniel Król Department of Technology, State."— Presentation transcript:
„B I R D S M O N D” BIRD SOUND MONITORING DATABASE Robert Wielgat, Agnieszka Lisowska-Lis, Tomasz Potempa, Daniel Król Department of Technology, State Higher Vocational School in Tarnów, Paweł Kozioł Complex of Foothills Landscape Parks in Tarnów Zbigniew Bonczar, Damian Wiehle, Marcin Lis Department of Zoology and Ecology, University of Agriculture in Kraków Kazimierz Walasz Institute of Environmental Sciences, Jagiellonian University in Kraków Antoni Ligęza, Tomasz Zieliński AGH University of Science and Technology in Kraków
Reasons for avian monitoring 1. 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 Objectives The following task to accomplish are planned in the years 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 Area Monitored 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 Tarnów PWSZ 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 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 N Lanius collurio – red-backed shrike - L'averla piccola
THANK YOU VERY MUCH FOR YOUR ATTENTION For more information visit project website: Emberizza citrinella – Yellowhammer - Lo zigolo giallo Garrulus glandarius – Jay - La ghiandaia Emberizza citrinella – Yellowhammer - Lo zigolo giallo
Stationary Digital Recorder ADC LCD MICROCONTROLLER Keyboard FAT32 Broadband condenser Microphone x 4 Memory Card Real Time Clock DAC Alluring speakers Microphone Amplifier x 4 Power amplifier Return Wireless Transceiver Antenna
Mobile Digital Recorder Return ADC MICROCONTROLLER FAT32 Broadband condenser microphone x 4 Memory Card Real Time Clock DAC Headphones Microphone Amplifier x 4 Headphones amplifier LCDKeyboard Antenna 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 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.
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. iYiY iXiX BIRD VOICE X BIRD VOICE Y 1N 1 M DTW o1o1 o2o2 o3o3 o4o4 o5o5 o6o6 a 23 a 22 b 2 (o 1 ) b 2 (o 2 ) b 2 (o 3 ) b 4 (o 5 )b 3 (o 4 )b 4 (o 6 ) a 34 a 45 a 12 a 33 a 44 HMM
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.
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 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.
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
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
Roles – Expert and Administrator Return Expert or Administrator Expert 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;