Towards Automatic Large-Scale Identification of Birds in Audio Recordings

This paper presents a computer-based technique for bird species identification at large scale. It automatically identifies multiple species simultaneously in a large number of audio recordings and provides the basis for the best scoring submission to the LifeCLEF 2014 Bird Identification Task. The method achieves a Mean Average Precision of 51.1% on the test set and 53.9% on the training set with an Area Under the Curve of 91.5% during cross-validation. Besides a general description of the underlying classification approach a number of additional research questions are addressed regarding the choice of features, selection of classifier hyperparameters and method of classification.