Bird song is essential for communication, especially for mate attraction and territory defense (Catchpole & Slater, 2008). The importance of birds’ vocalizations cannot be overstated. The ability to automatically analyze bird vocalizations would greatly benefit zoologists in their behavioral and ecological studies. Editors CommentsĮditors Comments go here. The authors declare no competing interest. Syllables for which YIN-bird is not suitable for are also described. YIN-bird optimizes YIN to improve pitch tracking performance of bird vocalizations. A well-known algorithm, YIN, accurately tracks the pitch of human speech, but is susceptible to octave errors when tracking bird song.
This paper also presents YIN-bird an improved pitch tracker for birds. This paper reports pitch tracking performance on different syllable types of bird vocalizations. Scientists sometimes extract pitch without knowledge of how well pitch trackers perform on bird song. A common way to quantify difference between bird populations is to analyze the pitch of bird song.
A lesser reported topic is the analysis of bird songs from subspecies of the same bird. Much of the reported research has concentrated on the identification of bird species from their songs or calls. The analysis of bird song has increased in the speech processing community in the past five years. A qualitative analysis showing YIN-bird not to be suitable for more complex bird vocalizations, such as nasals, is also presented.
This data-set was evaluated by expert listeners and described as “sounding like original & can hardly tell it is synthetic”. Gross pitch errors on whistles and trills were reduced by up to 4% on a ground truth data-set of synthetic bird song with known pitch. This paper presents YIN-bird, a modified version of YIN which exploits spectrogram properties to automatically set a minimum fundamental frequency parameter for YIN. YIN is a PDA which estimates pitch of human speech very well. Carefully tuned parameters improve pitch tracking with YIN, but optimal parameters can change quickly even within one song. The presence of multiple partials or tones simultaneously, extended frequency sweeps through multiple octaves, and rapid pitch modulations are just some of the difficulties encountered when estimating the pitch of bird song. This paper discusses pitch estimation performance on a variety of common bird vocalizations. Pitch detection algorithms (PDAs) proven to work on human speech may not be suitable for all types of bird vocalizations. To use pitch as a feature, researchers need confidence in their pitch extraction system. Pitch or fundamental frequency is an important feature of bird song, from which scientists can learn much about a population.
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