The Voice of Emotion across Species: How Do Human Listeners Recognize Animals' Affective States?
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{"title"=>"The voice of emotion across species: How do human listeners recognize animals' affective states?", "type"=>"journal", "authors"=>[{"first_name"=>"Marina", "last_name"=>"Scheumann", "scopus_author_id"=>"6507997403"}, {"first_name"=>"Anna S.", "last_name"=>"Hasting", "scopus_author_id"=>"16032707100"}, {"first_name"=>"Sonja A.", "last_name"=>"Kotz", "scopus_author_id"=>"7005961609"}, {"first_name"=>"Elke", "last_name"=>"Zimmermann", "scopus_author_id"=>"7101967838"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84897980217", "pmid"=>"24621604", "pui"=>"372799596", "isbn"=>"1932-6203", "scopus"=>"2-s2.0-84897980217", "doi"=>"10.1371/journal.pone.0091192", "issn"=>"19326203"}, "id"=>"10e4ed71-6104-3e0f-aa38-9e0889dccf34", "abstract"=>"Voice-induced cross-taxa emotional recognition is the ability to understand the emotional state of another species based on its voice. In the past, induced affective states, experience-dependent higher cognitive processes or cross-taxa universal acoustic coding and processing mechanisms have been discussed to underlie this ability in humans. The present study sets out to distinguish the influence of familiarity and phylogeny on voice-induced cross-taxa emotional perception in humans. For the first time, two perspectives are taken into account: the self- (i.e. emotional valence induced in the listener) versus the others-perspective (i.e. correct recognition of the emotional valence of the recording context). Twenty-eight male participants listened to 192 vocalizations of four different species (human infant, dog, chimpanzee and tree shrew). Stimuli were recorded either in an agonistic (negative emotional valence) or affiliative (positive emotional valence) context. Participants rated the emotional valence of the stimuli adopting self- and others-perspective by using a 5-point version of the Self-Assessment Manikin (SAM). Familiarity was assessed based on subjective rating, objective labelling of the respective stimuli and interaction time with the respective species. Participants reliably recognized the emotional valence of human voices, whereas the results for animal voices were mixed. The correct classification of animal voices depended on the listener's familiarity with the species and the call type/recording context, whereas there was less influence of induced emotional states and phylogeny. Our results provide first evidence that explicit voice-induced cross-taxa emotional recognition in humans is shaped more by experience-dependent cognitive mechanisms than by induced affective states or cross-taxa universal acoustic coding and processing mechanisms.", "link"=>"http://www.mendeley.com/research/voice-emotion-across-species-human-listeners-recognize-animals-affective-states", "reader_count"=>86, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>5, "Researcher"=>22, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>1, "Student > Master"=>19, "Other"=>2, "Student > Bachelor"=>6, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>5, "Researcher"=>22, "Student > Ph. D. Student"=>20, "Student > Postgraduate"=>1, "Student > Master"=>19, "Other"=>2, "Student > Bachelor"=>6, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Engineering"=>1, "Agricultural and Biological Sciences"=>33, "Medicine and Dentistry"=>4, "Neuroscience"=>5, "Arts and Humanities"=>3, "Veterinary Science and Veterinary Medicine"=>2, "Chemical Engineering"=>1, "Psychology"=>20, "Computer Science"=>3, "Earth and Planetary Sciences"=>1, "Linguistics"=>5}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Neuroscience"=>{"Neuroscience"=>5}, "Psychology"=>{"Psychology"=>20}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>33}, "Computer Science"=>{"Computer Science"=>3}, "Linguistics"=>{"Linguistics"=>5}, "Unspecified"=>{"Unspecified"=>8}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>3}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>2}}, "reader_count_by_country"=>{"Austria"=>1, "Hungary"=>2, "United States"=>1, "Japan"=>2, "United Kingdom"=>4, "Chile"=>1, "Germany"=>2}, "group_count"=>3}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/1416594"], "description"=>"<p>Mean and standard deviation of the (A) species recognition index and the (B) assumed familiarity index for each playback category.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Animal behavior", "neuroscience", "Cognitive neuroscience", "cognition", "Decision making", "Sensory perception", "Psychoacoustics", "Behavioral neuroscience", "Learning and memory", "Zoology", "psychology", "behavior", "emotions", "ratings", "playback"], "article_id"=>959195, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Marina Scheumann", "Anna S. Hasting", "Sonja A. Kotz", "Elke Zimmermann"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091192.g002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Familiarity_ratings_for_the_playback_categories_/959195", "title"=>"Familiarity ratings for the playback categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:00:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416593"], "description"=>"<p>Sonograms of examples of playback stimuli of the eight playback categories.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Animal behavior", "neuroscience", "Cognitive neuroscience", "cognition", "Decision making", "Sensory perception", "Psychoacoustics", "Behavioral neuroscience", "Learning and memory", "Zoology", "psychology", "behavior", "emotions", "examples", "playback", "stimuli"], "article_id"=>959194, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Marina Scheumann", "Anna S. Hasting", "Sonja A. Kotz", "Elke Zimmermann"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091192.g001", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sonograms_of_examples_of_playback_stimuli_of_the_eight_playback_categories_/959194", "title"=>"Sonograms of examples of playback stimuli of the eight playback categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:00:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416596"], "description"=>"<p>Mean ± standard deviation of following acoustic parameters: STIM DUR  =  duration of the stimulus (seconds), CALL DUR  =  percentage of time of the calls in the whole stimulus (%), No. VOC  =  number of calls in the stimulus; PEAK  =  peak frequency (Hz), MEAN f0  =  mean fundamental frequency (f0, Hz), SD f0  =  standard deviation of f0 (Hz), %VOI  =  percentage of voiced frames in the stimulus (%).</p>", "links"=>[], "tags"=>["Evolutionary biology", "Animal behavior", "neuroscience", "Cognitive neuroscience", "cognition", "Decision making", "Sensory perception", "Psychoacoustics", "Behavioral neuroscience", "Learning and memory", "Zoology", "psychology", "behavior", "emotions", "characterization", "playback"], "article_id"=>959197, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Marina Scheumann", "Anna S. Hasting", "Sonja A. Kotz", "Elke Zimmermann"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091192.t002", "stats"=>{"downloads"=>5, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Acoustic_characterization_of_the_playback_categories_/959197", "title"=>"Acoustic characterization of the playback categories.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-12 03:00:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416595"], "description"=>"<p>Mean and standard deviation of the valence index for the playback categories of the (A) self-perspective and the (B) others- perspective. one-sample t-test *** p≤0.001, **p≤0.01, *p≤0.05.</p>", "links"=>[], "tags"=>["Evolutionary biology", "Animal behavior", "neuroscience", "Cognitive neuroscience", "cognition", "Decision making", "Sensory perception", "Psychoacoustics", "Behavioral neuroscience", "Learning and memory", "Zoology", "psychology", "behavior", "emotions", "ratings", "playback"], "article_id"=>959196, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Marina Scheumann", "Anna S. Hasting", "Sonja A. Kotz", "Elke Zimmermann"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091192.g003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Valence_ratings_for_the_playback_categories_/959196", "title"=>"Valence ratings for the playback categories.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-03-12 03:00:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/1416598"], "description"=>"<div><p>Voice-induced cross-taxa emotional recognition is the ability to understand the emotional state of another species based on its voice. In the past, induced affective states, experience-dependent higher cognitive processes or cross-taxa universal acoustic coding and processing mechanisms have been discussed to underlie this ability in humans. The present study sets out to distinguish the influence of familiarity and phylogeny on voice-induced cross-taxa emotional perception in humans. For the first time, two perspectives are taken into account: the self- (i.e. emotional valence induced in the listener) versus the others-perspective (i.e. correct recognition of the emotional valence of the recording context). Twenty-eight male participants listened to 192 vocalizations of four different species (human infant, dog, chimpanzee and tree shrew). Stimuli were recorded either in an agonistic (negative emotional valence) or affiliative (positive emotional valence) context. Participants rated the emotional valence of the stimuli adopting self- and others-perspective by using a 5-point version of the Self-Assessment Manikin (SAM). Familiarity was assessed based on subjective rating, objective labelling of the respective stimuli and interaction time with the respective species. Participants reliably recognized the emotional valence of human voices, whereas the results for animal voices were mixed. The correct classification of animal voices depended on the listener's familiarity with the species and the call type/recording context, whereas there was less influence of induced emotional states and phylogeny. Our results provide first evidence that explicit voice-induced cross-taxa emotional recognition in humans is shaped more by experience-dependent cognitive mechanisms than by induced affective states or cross-taxa universal acoustic coding and processing mechanisms.</p></div>", "links"=>[], "tags"=>["Evolutionary biology", "Animal behavior", "neuroscience", "Cognitive neuroscience", "cognition", "Decision making", "Sensory perception", "Psychoacoustics", "Behavioral neuroscience", "Learning and memory", "Zoology", "psychology", "behavior", "emotions", "listeners", "affective"], "article_id"=>959199, "categories"=>["Biological Sciences", "Sociology"], "users"=>["Marina Scheumann", "Anna S. Hasting", "Sonja A. Kotz", "Elke Zimmermann"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0091192", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Voice_of_Emotion_across_Species_How_Do_Human_Listeners_Recognize_Animals_Affective_States_/959199", "title"=>"The Voice of Emotion across Species: How Do Human Listeners Recognize Animals' Affective States?", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-03-12 03:00:48"}

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