A set of functions to analyze sound time series developed in python

C. JARNE

San Luis

Conferencia; PyData; 2017

INSTITUTO DE MATEMATICA APLICADA DE SAN LUIS

When an experimental data analysis is perform for a scientific experiment it is very common to develop custom software to perform the task. Depending on the paper focus, journal scope or the results, most of the time not all the code or ideas develop during the work are presented or described in the paper. In this work the idea is to present a set of four simple algorithms and the code implementations in python related to time series analysis of sound related data extracted from bird songs. In this selection the first algorithm is an heuristic and simple way to obtain signal envelop and the code implementation. The second one is an algorithm to obtain fundamental frequency for tonal sounds. The third one consists in a way to align similar signals using correlation. The last one is related to syllable individualization.