On Using Prefiltration in HMM-Based Bird Species Recognition

被引:7
|
作者
Wielgat, Robert [1 ]
Swietojanski, Pawel [1 ]
Potempa, Tomasz [1 ]
Krol, Daniel [1 ]
机构
[1] Higher State Vocat Sch Tarnow, Dept Technol, Mickiewicza 8, PL-33100 Tarnow, Poland
关键词
D O I
10.1109/ICSES.2012.6382258
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
下载
收藏
页数:5
相关论文
共 50 条
  • [1] BIRD SPECIES RECOGNITION FROM FIELD RECORDINGS USING HMM-BASED MODELLING OF FREQUENCY TRACKS
    Jancovic, Peter
    Koekueer, Muenevver
    Russell, Martin
    2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2014,
  • [2] BIRD SPECIES RECOGNITION USING HMM-BASED UNSUPERVISED MODELLING OF INDIVIDUAL SYLLABLES WITH INCORPORATED DURATION MODELLING
    Jancovic, Peter
    Kokuer, Munevver
    Zakeri, Masoud
    Russell, Martin
    2016 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING PROCEEDINGS, 2016, : 559 - 563
  • [3] HMM-BASED MODELLING OF INDIVIDUAL SYLLABLES FOR BIRD SPECIES RECOGNITION FROM AUDIO FIELD RECORDINGS
    Jancovic, Peter
    Zakeri, Masoud
    Kokuer, Munevver
    Russell, Martin
    2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 768 - 772
  • [4] Recognition of Multiple Bird Species based on Penalised Maximum Likelihood and HMM-based Modelling of Individual Vocalisation Elements
    Jancovic, Peter
    Kokuer, Munevver
    17TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2016), VOLS 1-5: UNDERSTANDING SPEECH PROCESSING IN HUMANS AND MACHINES, 2016, : 2612 - 2616
  • [5] HMM-Based Speech Recognition Using Adaptive Framing
    Goh, Yeh-Huann
    Raveendran, Paramesran
    TENCON 2009 - 2009 IEEE REGION 10 CONFERENCE, VOLS 1-4, 2009, : 226 - 230
  • [6] HMM-based action recognition using contour histograms
    Angeles Mendoza, M.
    Perez de la Blanca, Nicolas
    PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 1, PROCEEDINGS, 2007, 4477 : 394 - +
  • [7] An HMM-based speech recognition IC
    Han, W
    Hon, KW
    Chan, CF
    Lee, T
    Choy, CS
    Pun, KP
    Ching, PC
    PROCEEDINGS OF THE 2003 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOL II: COMMUNICATIONS-MULTIMEDIA SYSTEMS & APPLICATIONS, 2003, : 744 - 747
  • [8] The advantage of using an HMM-based approach for faxed word recognition
    Elms A.J.
    Procter S.
    Illingworth J.
    International Journal on Document Analysis and Recognition, 1998, 1 (1) : 18 - 36
  • [9] An HMM-based character recognition network using level building
    Kim, HJ
    Kim, SK
    Kim, KH
    Lee, JK
    PATTERN RECOGNITION, 1997, 30 (03) : 491 - 502
  • [10] Named entity recognition using an HMM-based chunk tagger
    Zhou, GD
    Su, J
    40TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, PROCEEDINGS OF THE CONFERENCE, 2002, : 473 - 480