Bird Species Recognition Using Unsupervised Modeling of Individual Vocalization Elements
نویسندگان
چکیده
منابع مشابه
Studies on Bird Vocalization Detection and Classification of Species
Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Seppo Fagerlund Name of the doctoral dissertation Studies on Bird Vocalization Detection and Classification of Species Publisher School of Electrical Engineering Unit Department of Signal Processing and Acoustics Series Aalto University publication series DOCTORAL DISSERTATIONS 166/2014 Manuscript submitted 12 June 2014 Date o...
متن کاملBird Species Recognition Using Support Vector Machines
Automatic identification of bird species by their vocalization is studied in this paper. Bird sounds are represented with two different parametric representations: (i) the mel-cepstrum parameters and (ii) a set of low-level signal parameters, both of which have been found useful for bird species recognition. Recognition is performed in a decision tree with support vector machine (SVM) classifie...
متن کاملRecognition of Multiple Bird Species Based on Penalised Maximum Likelihood and HMM-Based Modelling of Individual Vocalisation Elements
This paper presents an extension of our recent work on recognition of multiple bird species from their vocalisations by incorporating an improved acoustic modelling. The acoustic scene is segmented into spectro-temporal isolated segments by employing a sinusoidal detection algorithm, which is able to handle multiple simultaneous bird vocalisations. Each segment is represented as a temporal sequ...
متن کاملFrom Bird Species to Individual Songs Recognition: Automated Methods for Localization and Recognition in Real Habitats Using Wireless Sensor Networks
The recent advances in wireless networked sensing systems, combined with the ever increasing computational power of embedded systems has brought field biologists a large palette of opportunities for automated analysis of ecosystems. Now phenomena can be observed in real time and at their heart, where they happen. Our work presents such an attempt at combining wireless sensors with automated det...
متن کاملUnsupervised Acoustic Classification of Bird Species Using Hierarchical Self-organizing Maps
In this paper, we propose the application of hierarchical self-organizing maps to the unsupervised acoustic classification of bird species. We describe a series of experiments on the automated categorization of tropical antbirds from their songs. Experimental results showed that accurate classification can be achieved using the proposed model. In addition, we discuss how categorization capabili...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE/ACM Transactions on Audio, Speech, and Language Processing
سال: 2019
ISSN: 2329-9290,2329-9304
DOI: 10.1109/taslp.2019.2904790