Related articles and software

automated classification of birdsong elements

with support vector machines Tachibana, Ryosuke O., Naoya Oosugi, and Kazuo Okanoya. “Semi-automatic classification of birdsong elements using a linear support vector machine.” PloS one 9.3 (2014): e92584. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0092584

with convolutional neural nets Koumura, Takuya, and Kazuo Okanoya. “Automatic Recognition of Element Classes and Boundaries in the Birdsong with Variable Sequences.” PloS one 11.7 (2016): e0159188. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0159188 https://github.com/cycentum/birdsong-recognition

with k-nearest neighbors Songbrowser. Troyer lab. http://www.utsa.edu/troyerlab/software.html

semi-automated clustering methods

Daou, Johnson, Wu, Bertram. “A Computational Tool for Automated Large-Scale Analysis and Measurement of Bird-Song Syntax” Journal of Neuroscience Methods, 210:147-160, 2012. http://www.sciencedirect.com/science/article/pii/S0165027012002841 http://www.math.fsu.edu/~bertram/software/birdsong/

Burkett, Zachary D., et al. “VoICE: A semi-automated pipeline for standardizing vocal analysis across models.” Scientific reports 5 (2015). https://www.ibp.ucla.edu/research/white/CODE.html

automated analysis and similarity scores

Tchernichovski, O., Nottebohm, F., Ho, C.E., Bijan, P., Mitra, P.P. “A procedure for an automated measurement of song similarity.” Animal Behaviour 59 (2000): 1167-1176 http://soundanalysispro.com/

Mandelblat-Cerf, Yael, and Michale S. Fee. “An automated procedure for evaluating song imitation.” PloS one 9.5 (2014): e96484. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0096484#s6 code: https://doi.org/10.1371/journal.pone.0096484.s002

Mets, David Gavin, and Michael S. Brainard. “An Automated Approach to the Quantitation of Vocalizations and Vocal Learning in the Songbird.” bioRxiv (2017): 166124. https://www.biorxiv.org/content/early/2017/07/20/166124

Soderstrom, Ken, and Ali Alalawi. “Software for objective comparison of vocal acoustic features over weeks of audio recording: KLFromRecordingDays.” SoftwareX 6 (2017): 271-277. http://www.sciencedirect.com/science/article/pii/S2352711017300523 code: https://github.com/soderstromk/KLFromRecordingDays