July | 2017 | CENTRE OF COGNITIVE ETHOLOGY

2017

Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Průchová, Pavel Linhart, Ludek Muller, Dana Jirotkova

Abstract:

One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.

2017

Alexandra Průchová, Pavel Jaška, Pavel Linhart

doi:10.1007/s10336-017-1455-6

Abstract:

Individual variation in vocalizations has been widely studied among different animal taxa, and it is commonly reported that vocalizations could be potentially used to monitor individuals in many species. Songbirds represent a challenging group of animals for the study of signalling of individual identity. They are highly vocal, but their songs are complex and can change over time. In this study, we tested whether general song characteristics, which are independent of song type, can be used to discriminate and consistently identify Chiffchaff males within and between days and between years. There was individual variation in songs of recorded Chiffchaffs, and it was possible to easily discriminate between males at any one point in time. However, the level of re-identification of males across days and years was low. For effective identification it was necessary to compare songs of a single song type. However, Chiffchaffs haphazardly switch among song types, sometimes singing the same song type for a long time, making it difficult to collect equivalent song types or to sample the birds’ full repertoires. For example, 5-min recordings of males taken in different years did not contain equivalent song types, leading to low identification success. Although we were not successful in the re-identification of males based on general song characteristics, we discuss methods of acoustic identification which are not dependent on song repertoire content and are potentially valuable tools for the study of species such as the Chiffchaff.