Children can read dog barks better than adults
October 14th, 2011 - 4:05 pm ICT by IANSLondon, Oct 14 (IANS) Scientists have found that 10-year-olds can interpret subtle noises made by dogs while adults find it easiest to distinguish when a dog is angry.
These results came from playing recordings of various bark ‘modes’ - such as warning off a stranger, playing and feeling lonely - to children aged six, eight and 10, and adults, and asking them to pair the noises with corresponding human facial expressions, the Daily Mail reports.
Study authors Peter Pongracz and Csaba Molnár from Eotvos Lorand University in Budapest, said: “This shows that the ability of understanding basic inner states of dogs on the basis of acoustic signals is present in humans from a very young age.”
“These results are in sharp contrast with other reports in the literature which showed that young children tend to misinterpret canine visual signals.”
Molnár’s other research in the field includes using machine-learning algorithms in an effort to further understand how humans ‘listen’ to dog barks.
Molnár and colleagues’ tested a computer algorithm’s ability to identify and differentiate the acoustic features of dog barks, and classify them according to different contexts and individual dogs.
The software analysed more than 6,000 barks from 14 Hungarian sheepdogs (Mudi breed) in six different situations: ’stranger’, ‘fight’, ‘walk’, ‘alone’, ‘ball’ and ‘play’.
The barks were recorded with a tape recorder before being transferred to the computer, where they were digitised and individual bark sounds were coded, classified and evaluated.
The software could reliably discriminate among individual dogs while humans cannot — which suggests that there are individual differences in barks of dogs even though humans are not able to recognise them.
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Tags: 10 year olds, acoustic features, acoustic signals, computer algorithm, csaba, daily mail, different contexts, dog barks, eotvos lorand university, human facial expressions, hungarian sheepdogs, individual differences, inner states, machine learning algorithms, mail reports, pongracz, stranger, study authors, tape recorder, visual signals