期刊文献+

野生动物鸣声数据管理系统设计与实现 被引量:1

Design and Implementation of the Data Management System for Wild Animal Acoustics
下载PDF
导出
摘要 为了有效管理野外采集的高通量长时间序列野生动物鸣声数据,设计野生动物鸣声数据管理系统的总体架构与主要功能模块,提出文件分级管理体系用于统一管理原始音频文件与处理结果文件,并进行系统主要功能的开发。系统有效保持了声音数据的完整性,在对数据进行层次化管理的基础上提供了高效的检索能力,能够满足相关领域研究中对数据有效利用的需求。 In order to manage the high-throughput and long-term series of wild animal acoustic data collected in the wild,this papere designed the overall architecture and main functional modules of the wild animal acoustic data management system,proposeda file hierarchical management pattern for unified management of original audio files and processed result files.In addition,this paper explained the main functions of the system.The system maintained the originality of sound data,provided efficient retrieval capabilities on the basis of layering management of the data,so as tomeet the demand of making effective use of data for related work.
作者 杨铭伦 于新文 张旭 欧阳萱 侯亚男 高家军 YANG Minglun;YU Xinwen;ZHANG Xu;OUYANG Xuan;HOU Yanan;GAO Jiajun(Institute of resource information,Chinese Academy of Forestry,Beijing 100091,China)
出处 《林业资源管理》 北大核心 2021年第6期124-129,共6页 Forest Resources Management
基金 中央级公益性科研院所基本科研业务费专项资金“基于声音指数的生物多样性监测技术研究”(CAFYBB2018SZ010)。
关键词 动物鸣声数据 处理结果数据 高通量数据管理 管理系统 animal acoustic data processing data high-throughput data management management system
  • 相关文献

参考文献5

二级参考文献39

  • 1Somervuo P, Hanna A. Bird song recognition based on syllable pair histograms[ A]. IEEE International Conference on Acous- tics, Speech, and Signal Processing [ C ]. Monlreal, Canada: lF.F.F. Press,2004:825 - 828.
  • 2Cheng J,Sun Y,Ji L.A call-independent and automatic acous- tic system for the individual recognition of animals: a novel model using four passerines [ J]. Pattern Recognition, 2010, 43 (11) :3846- 3852.
  • 3Chu W, et al. Noise robust bird song detection using syllable pattern-based hidden markov models [ A ]. 1EEE International Conference on Acoustics, Speech, and Signal Processing [ C ]. Prague, Czech Republic: IEEE Press, 2011:345- 348.
  • 4Bardeli R, Wolff D, F, et al. Detecting bird sounds in a complex acoustic envirommnt and application to bioacoustic mon- itodng [ J]. Pattem Recognition letters,2010,31 (12) : 1524 - 1534.
  • 5Kim C, Stem R. Feature extraction for robust speech recognition based on maximizing the sharpness of the power distribution and on power flooring [ A ]. IF.I.E International Conference on Acoustics, Speech, and Signal Processing[ C]. Dallas, TX: IEEE Press, 2010.4574 - 4577.
  • 6Rangachari S, Loizou P C. A noise estimation algorithm for highly non-stationary environments [ J ]. Speech Communica- tion,2006,48(2) :220 - 231.
  • 7Kamath S, et al. A multi-band spectral subtraction method for enhancing speech corrupted by colored noise[ A]. 1EEE Interna- tional Conference on Acoustics, Speech, and Signal Processing [ C ]. Orlando, FL: 1EEE Press, 2002. IV-4164-1V-4164.
  • 8Slaney M.Auditory toolbox version 2 [ CP/OL]. https://en- gineering, purdue, edu/- malcolm/interval/1998-010/Audito- ryToolbox, zip, 2012-5-14.
  • 9Universitat Pompeu Fabra. Repository of sound under the cre- ative commons license, Freesound. org [ DB/OL ]. http:// www. freesound, org, 2012-5-14.
  • 10Chang C C,Lin C J. Libsvm version 3.12 [ CP/OL]. http:// www. csie. ntu. edu. tw/- cjlin/libsvm/ libsvm-3.12, zip, 2012-5-14.

共引文献70

同被引文献10

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部