Is Birdsong More Like Speech or Music?

doi:10.1016/j.tics.2016.02.004

Trends in Cognitive Sciences

Volume 20, Issue 4, April 2016, Pages 245-247

https://doi.org/10.1016/j.tics.2016.02.004 Get rights and content

Music and speech share many acoustic cues but not all are equally important. For example, harmonic pitch is essential for music but not for speech. When birds communicate is their song more like speech or music? A new study contrasting pitch and spectral patterns shows that birds perceive their song more like humans perceive speech.

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There are more references available in the full text version of this article.

Cited by (12)

Agnosia for bird calls
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Citation Excerpt :
To determine the true selectivity of BA's agnosia within the auditory modality would require a more detailed assessment of auditory apperceptive processing and semantic processing of other categories of sounds. In particular, it would be of interest to assess his ability to recognise familiar melodies, particularly given the interesting formal and cognitive similarities of birdsong to human music (and indeed, speech: Shannon, 2016). This parallel analysis could potentially extend to judgements on emotional content, as bird calls (like melodies, but unusually for a specific class of environmental sounds) vary widely in affective content and potentially, other associations.
The cognitive organisation of nonverbal auditory knowledge remains poorly defined. Deficits of environmental sound as well as word and visual object knowledge are well-recognised in semantic dementia. However, it is unclear how auditory cognition breaks down in this disorder and how this relates to deficits in other knowledge modalities. We had the opportunity to study a patient with a typical syndrome of semantic dementia who had extensive premorbid knowledge of birds, allowing us to assess the impact of the disease on the processing of auditory in relation to visual and verbal attributes of this specific knowledge category. We designed a novel neuropsychological test to probe knowledge of particular avian characteristics (size, behaviour [migratory or nonmigratory], habitat [whether or not primarily water-dwelling]) in the nonverbal auditory, visual and verbal modalities, based on a uniform two-alternative-forced-choice procedure. The patient's performance was compared to healthy older individuals of similar birding experience. We further compared his performance on this test of bird knowledge with his knowledge of familiar human voices and faces. Relative to healthy birder controls, the patient showed marked deficits of bird call and bird name knowledge but relatively preserved knowledge of avian visual attributes and retained knowledge of human voices and faces. In both the auditory and visual modalities, his knowledge of the avian characteristics of size and behaviour was intact whereas his knowledge of the associated characteristic of habitat was deficient. This case provides further evidence that nonverbal auditory knowledge has a fractionated organisation that can be differentially targeted in semantic dementia.
Automated bird acoustic event detection and robust species classification
2017, Ecological Informatics
Non-invasive bioacoustic monitoring is becoming increasingly popular for biodiversity conservation. Two automated methods for acoustic classification of bird species currently used are frame-based methods, a model that uses Hidden Markov Models (HMMs), and event-based methods, a model consisting of descriptive measurements or restricted to tonal or harmonic vocalizations. In this work, we propose a new method for automated field recording analysis with improved automated segmentation and robust bird species classification. We used a Gaussian Mixture Model (GMM)-based frame selection with an event-energy-based sifting procedure that selected representative acoustic events. We employed a Mel, band-pass filter bank on each event's spectrogram. The output in each subband was parameterized by an autoregressive (AR) model, which resulted in a feature consisting of all model coefficients. Finally, a support vector machine (SVM) algorithm was used for classification. The significance of the proposed method lies in the parameterized features depicting the species-specific spectral pattern. This experiment used a control audio dataset and real-world audio dataset comprised of field recordings of eleven bird species from the Xeno-canto Archive, consisting of 2762 bird acoustic events with 339 detected “unknown” events (corresponding to noise or unknown species vocalizations). Compared with other recent approaches, our proposed method provides comparable identification performance with respect to the eleven species of interest. Meanwhile, superior robustness in real-world scenarios is achieved, which is expressed as the considerable improvement from 0.632 to 0.928 for the F-score metric regarding the “unknown” events. The advantage makes the proposed method more suitable for automated field recording analysis.
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Trends in Cognitive Sciences

SpotlightIs Birdsong More Like Speech or Music?

Cognition

Songbirds use spectral shape, not pitch, for sound pattern recognition

Proc. Natl. Acad. Sci. U.S.A.

Chimaeric sounds reveal dichotomies in auditory perception

Nature

Speech recognition with primarily temporal cues

Science

Spotlight
Is Birdsong More Like Speech or Music?