کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4374752 1617199 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identification of European woodpecker species in audio recordings from their drumming rolls
ترجمه فارسی عنوان
شناسایی گونه های دارکوب اروپائی در ضبط صدا از تعداد دفعات نوک زنی آنها
کلمات کلیدی
دارکوب؛ ضربت زنی؛ شناسایی گونه؛ تقسیم بندی؛ کاهش ابعاد تی SNE . ویژگی های صوتی
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی


• European woodpecker species can be identified from their drumming sounds.
• Not all bird sounds respond well to state-of-the-art classification techniques.
• Temporal acoustic features specific to drumming were implemented.
• 87.2% of 2665 drumming rolls were correctly classified using k-NN.
• This opens new avenues for the monitoring of woodpeckers in the wild.

Drumming sounds are substantial clues when searching audio recordings for the presence of woodpeckers. Woodpeckers use drumming for territory defence and mate attraction to such an extent that some species have no vocalisations for these functions. This implies that drumming bears species markers. This hypothesis stands at the root of our project to develop an autonomous program for the identification of drumming species. To proceed, we assembled a database of 361 recordings from open-access bird sound archives. The recordings were for nine drumming species found on the European continent. Focusing on the signal below 1500 Hz, we reviewed all audio files and extracted 2665 drumming rolls. For recordings where multiple birds were present, the drumming rolls were attributed to individual birds. This allowed keeping track of the time interval between successive rolls. The characteristic traits of drumming are decidedly temporal. Consequently, the spectral features that have been successful in other recent bird identification studies were not applicable in our case. We developed specialized drumming parameters and automated their calculation. We then performed a t-SNE dimensionality reduction to visualise the dataset and to demonstrate that our parameters detached the different classes properly. Eventually, a k-NN algorithm accurately labelled 87.2% of the submitted test samples. The time structure within the drumming rolls (speed, acceleration) provided the critical features. The duration of the rolls followed in importance. The results compare well to existing literature and attest to the feasibility of monitoring European woodpecker species by tracking drumming.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Informatics - Volume 35, September 2016, Pages 61–70
نویسندگان
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