Abstract
This study investigates how experience and gender influence the perception of emotions in dog barks. Drawing from Morton's structural-motivational rule and previous research on mammalian vocalizations, we aimed to discern whether humans, especially those experienced with dogs, can accurately identify emotions such as stranger, anger, lonely, and play in dog barks. Using recordings of Indian Lesser Spitz barks in various contexts, we conducted auditory-perceptual experiments with two groups: experienced listeners (with more than 2- 3 years of pet dog experience) and non-experienced listeners. Participants listened to bark sequences and identified the corresponding emotions. Results revealed that experienced listeners consistently outperformed non- experienced ones in identifying emotions, except for 'play,' where no significant difference was observed. Gender did not significantly affect emotion perception. Interestingly, 'anger' was most accurately identified across both groups, followed by 'stranger,' 'play,' and 'lonely' emotions. Analyzing open-ended responses, we found that acoustic cues such as pitch and inter-bark intervals strongly influenced emotional perception. 'Stranger' barks were described as low-pitched, while 'anger' barks had shorter inter-bark intervals. 'Lonely' barks were characterized by high pitch and longer inter- bark intervals than 'play' barks. These findings suggest that experience plays a crucial role in accurately perceiving emotions in dog barks, aligning with the concept of a common mammalian heritage in emotional communication. Gender differences were negligible in this context. Understanding the acoustic cues underlying emotional expression in dogs enhances our comprehension of canine behavior and has implications for fields like animal welfare and neuroscience. Further research could delve deeper into the mechanisms underlying emotional perception in non-verbal communication across mammalian species.
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More From: International Journal of Innovative Science and Research Technology (IJISRT)
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