Acoustic model adaptation for ortolan bunting (Emberiza hortulana L.) song-type classification

Automatic systems for vocalization classification often require fairly large amounts of data on which to train models. However, animal vocalization data collection and transcription is a difficult and time-consuming task, so that it is expensive to create large data sets. One natural solution to this problem is the use of acoustic adaptation methods. Such methods, common in human speech recognition systems, create initial models trained on speaker independent data, then use small amounts of adaptation data to build individual-specific models. Since, as in human speech, individual vocal variability is a significant source of variation in bioacoustic data, acoustic model adaptation is naturally suited to classification in this domain as well. To demonstrate and evaluate the effectiveness of this approach, this paper presents the application of maximum likelihood linear regression adaptation to ortolan bunting (Emberiza hortulana L.) song-type classification. Classification accuracies for the adapted system are computed as a function of the amount of adaptation data and compared to caller-independent and caller-dependent systems. The experimental results indicate that given the same amount of data, supervised adaptation significantly outperforms both caller-independent and caller-dependent systems

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks

Functional significance of cuckoo Cuculus canorus calls: responses of conspecifics, hosts and non-hosts

Male cuckoos Cuculus canorus produce calls that differ in number of syllables depending on environmental conditions and presence of male and female conspecifics. Why different males produce so repeatable calls that vary greatly in duration among males remains an open question. We used playback of cuckoo calls with few or many syllables (hereafter short and long calls), and woodpigeon calls (a control that also produces few or many syllables), predicting that playback of longer cuckoo calls should attract more male cuckoos (if males with such calls are dominant and successfully out-compete other males due to intraspecific competition), and attract more hosts mobbing male cuckoos (cuckoos with such calls and their females attract more hosts because of an increased risk of parasitism). Because cuckoos differentially parasitize hosts away from human habitation, we also tested whether the number of syllables in cuckoo calls differed with distance from buildings. Playback showed significant effects of number of syllables in cuckoo calls, but not woodpigeon Columba palumbus calls, with an additional effect of distance from human habitation decreasing the response to playback. These findings are consistent with the hypothesis that longer cuckoo calls, especially played back near human habitation, attract more conspecifics and hosts than shorter calls. To the best of knowledge this is the first study showing that cuckoo call response modified both other cuckoo individuals, as well as hosts response

Ortolan Buntings Emberiza hortulana mimicking other species and other dialects of own species

We present new acoustically well-documented observations of Ortolan Bunting males from Norway, singing atypical songs with syllables copied from other species and from non-neighbouring, distant populations of own species. The first case concerns a male singing strophes containing syllables of Yellowhammer and Ortolan Bunting, both most probably copied in central Europe. These songs often had broken syntax. The second case concerns a male that sang both typical strophes and strophes that had the initial part copied from a local dialect of Redwing, but with a typical syntax for the species. That male mated successfully. Causes and consequences of vocal mimicry in the species are discussed