Alle Publikationen
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2017
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(2017): Towards a social functional account of laughter. Acoustic features convey reward, affiliation, and dominance. In: PLoS one 12 (8). DOI: 10.1371/journal.pone.0183811
DOI: http://www.ncbi.nlm.nih.gov/pubmed/28850589 Abstract: Recent work has identified the physical features of smiles that accomplish three tasks fundamental to human social living: rewarding behavior, establishing and managing affiliative bonds, and negotiating social status. The current work extends the social functional account to laughter. Participants (N = 762) rated the degree to which reward, affiliation, or dominance (between-subjects) was conveyed by 400 laughter samples acquired from a commercial sound effects website. Inclusion of a fourth rating dimension, spontaneity, allowed us to situate the current approach in the context of existing laughter research, which emphasizes the distinction between spontaneous and volitional laughter. We used 11 acoustic properties extracted from the laugh samples to predict participants' ratings. Actor sex moderated, and sometimes even reversed, the relation between acoustics and participants' judgments. Spontaneous laughter appears to serve the reward function in the current framework, as similar acoustic properties guided perceiver judgments of spontaneity and reward: reduced voicing and increased pitch, increased duration for female actors, and increased pitch slope, center of gravity, first formant, and noisiness for male actors. Affiliation ratings diverged from reward in their sex-dependent relationship to intensity and, for females, reduced pitch range and raised second formant. Dominance displayed the most distinct pattern of acoustic predictors, including increased pitch range, reduced second formant in females, and decreased pitch variability in males. We relate the current findings to existing findings on laughter and human and non-human vocalizations, concluding laughter can signal much more that felt or faked amusement.
Keywords: Acoustics, Adult, Aged, Art der Beziehung zum Interaktionspartner, Belohnung, center of gravity, Dauer, Female, formant, Gender, Gestik/Mimik, Humans, Klanghöhe (pitch), Kommunikations-/Interaktionsprinzipien, Lächeln, Lachen, Laughter/psychology, Male, Middle Aged, noisiness, pitch slope, Reward, Sanktionierung, Sex Factors, Social Dominance, Social Identification, Soziale Distanz, Soziale Dominanz, Spontaneität beim Lachen, Status / biologische Marker, Stimmhaftigkeit (voicing), Young Adult, Zugehörigkeit (affiliation) 2014
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(2014) : A system for feature classification of emotions based on speech analysis; applications to human-robot interaction: 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM): Tehran, Iran: IEEE, S. 795-800
DOI: https://doi.org/10.1109/ICRoM.2014.6991001 Abstract: A system for recognition of emotions based on speech analysis can have interesting applications in human robot interaction. Robot should make a proper mutual communication between sound recognition and perception for creating a desired emotional interaction with humans. Advanced research in this field will be based on sound analysis and recognition of emotions in spontaneous dialog. In this paper, we report the results obtained from an exploratory study on a methodology to automatically recognize and classify basic emotional states. The study attempted to investigate the appropriateness of using acoustic and phonetic properties of emotive speech with the minimal use of signal processing algorithms. The efficiency of the methodology was evaluated by experimental tests on adult European speakers. The speakers had to repeat six simple sentences in English language in order to emphasize features of the pitch (peak, value and range), the intensity of the speech, the formants and the speech rate. The proposed methodology using the freeware program (PRAAT) and consists of generating and analyzing a graph of pitch, formant and intensity of speech signals for classify basic emotion. Eventually, the proposed model provided successful recognition of the basic emotion in most of the cases.
Keywords: acoustic properties, Acoustics, adult European speakers, Angemessen(heit) (von Technik), emotion feature classification, emotion recognition, emotional interaction, emotional state classification, emotional state recognition, emotive speech, English language, Feature extraction, formant, formants, graph analysis, graph generation, graph theory, human-robot interaction, ieee xplore, mutual communication, phonetic properties, pitch, pitch features, PRAAT freeware program, public domain software, Shape, signal classification, signal processing algorithms, sound analysis, sound perception, sound recognition, speech, speech analysis, speech intensity, speech rate, speech recognition, speech signals, spontaneous dialog
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