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Bird Chirps Annotation UsingTime-Frequency Domain Analysis
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

There are around 10,426 bird species around the world. Recognizing the bird species for an untrained person is almost impossible either

by watching or listening them. In order to identify the bird species

from their sounds, there is a need for an application that can detect

the bird species from its sound. Time-frequency domain analysis techniques are used to implement the application. We implemented two

time-frequency domain feature extraction methods.

In feature extraction, a signature matrix which consist of extracted

features is created for bird sound signals. A database of signature matrix is created with bird chirps extracted features. We implemented

two feature classification methods. They are auto-correlation feature classification method and reference difference feature classification method. An unknown bird chirp is compared with the database

to detect the species name. The main aim of the research is to implement the time-frequency domain feature extraction method, create a

signature matrix database, implement two feature classification methods and compare them.

At last, bird species were identified in the research and the auto-correlation classification method detects the bird species better than

the reference difference classification method.

Place, publisher, year, edition, pages
2016. , 51 p.
Keyword [en]
Bird Species Detection, Correlation, Identification, Time- Frequency Analysis, Signature Matrix
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-13624OAI: oai:DiVA.org:bth-13624DiVA: diva2:1057294
Educational program
ETASX Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Presentation
2016-10-28, J3506, 10:00 (English)
Supervisors
Examiners
Available from: 2016-12-22 Created: 2016-12-16 Last updated: 2016-12-22Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
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