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- Juslin, Patrik N, 1969-, et al.
(författare)
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Speech emotion analysis
- 2008. - 3
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Ingår i: Scholarpedia. - : Scholarpedia. ; , s. 4240-
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Bokkapitel (populärvet., debatt m.m.)abstract
- Speech emotion analysis refers to the use of various methods to analyze vocal behavior as a marker of affect (e.g., emotions, moods, and stress), focusing on the nonverbal aspects of speech. The basic assumption is that there is a set of objectively measurable voice parameters that reflect the affective state a person is currently experiencing (or expressing for strategic purposes in social interaction). This assumption appears reasonable given that most affective states involve physiological reactions (e.g., changes in the autonomic and somatic nervous systems), which in turn modify different aspects of the voice production process. For example, the sympathetic arousal associated with an anger state often produce changes in respiration and an increase in muscle tension, which influence the vibration of the vocal folds and vocal tract shape, affecting the acoustic characteristics of the speech, which in turn can be used by the listener to infer the respective state (Scherer, 1986). Speech emotion analysis is complicated by the fact that vocal expression is an evolutionarily old nonverbal affect signaling system coded in an iconic and continuous fashion, which carries emotion and meshes with verbal messages that are coded in an arbitrary and categorical fashion. Voice researchers still debate the extent to which verbal and nonverbal aspects can be neatly separated. However, that there is some degree of independence is illustrated by the fact that people can perceive mixed messages in speech utterances – that is, that the words convey one thing, but that the nonverbal cues convey something quite different.
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- Patel, S., et al.
(författare)
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Acoustic markers of emotions based on voice physiology
- 2010
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Ingår i: Proceedings of the International Conference on Speech Prosody. - : International Speech Communications Association. - 9780000000002
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Konferensbidrag (refereegranskat)abstract
- Acoustic models of emotions may benefit from considering the underlying voice production mechanism. This study sought to describe emotional expressions according to physiological variations measured from the inverse-filtered glottal waveform in addition to standard parameter extraction. An acoustic analysis was performed on a subset of the /a/ vowels within the GEMEP database (10 speakers, 5 emotions). of the 12 acoustic features computed, repeated measures ANOVA showed significant main effects for 11 parameters. Subsequent principal components analysis revealed the three components that explain acoustic variations due to emotion, including “tension” (CQ, H1-H2, MFDR, LTAS) “perturbation” (jitter, shimmer, HNR), and “voicing” (fundamental frequency).
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- Scherer, K. R., et al.
(författare)
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The expression of emotion in the singing voice : Acoustic patterns in vocal performance
- 2017
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Ingår i: Journal of the Acoustical Society of America. - : Acoustical Society of America (ASA). - 0001-4966 .- 1520-8524. ; 142:4, s. 1805-1815
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Tidskriftsartikel (refereegranskat)abstract
- There has been little research on the acoustic correlates of emotional expression in the singing voice. In this study, two pertinent questions are addressed: How does a singer's emotional interpretation of a musical piece affect acoustic parameters in the sung vocalizations? Are these patterns specific enough to allow statistical discrimination of the intended expressive targets? Eight professional opera singers were asked to sing the musical scale upwards and downwards (using meaningless content) to express different emotions, as if on stage. The studio recordings were acoustically analyzed with a standard set of parameters. The results show robust vocal signatures for the emotions studied. Overall, there is a major contrast between sadness and tenderness on the one hand, and anger, joy, and pride on the other. This is based on low vs high levels on the components of loudness, vocal dynamics, high perturbation variation, and a tendency for high low-frequency energy. This pattern can be explained by the high power and arousal characteristics of the emotions with high levels on these components. A multiple discriminant analysis yields classification accuracy greatly exceeding chance level, confirming the reliability of the acoustic patterns.
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- Sundberg, Johan, et al.
(författare)
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Analyzing Emotion Expression in Singing via Flow Glottograms, Long-Term-Average Spectra, and Expert Listener Evaluation
- 2021
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Ingår i: Journal of Voice. - : Elsevier BV. - 0892-1997 .- 1873-4588. ; 35:1, s. 52-60
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Tidskriftsartikel (refereegranskat)abstract
- Background: Acoustic aspects of emotional expressivity in speech have been analyzed extensively during recent decades. Emotional coloring is an important if not the most important property of sung performance, and therefore strictly controlled. Hence, emotional expressivity in singing may promote a deeper insight into vocal signaling of emotions. Furthermore, physiological voice source parameters can be assumed to facilitate the understanding of acoustical characteristics. Method: Three highly experienced professional male singers sang scales on the vowel /ae/ or /a/ in 10 emotional colors (Neutral, Sadness, Tender, Calm, Joy, Contempt, Fear, Pride, Love, Arousal, and Anger). Sixteen voice experts classified the scales in a forced-choice listening test, and the result was compared with long-term-average spectrum (LTAS) parameters and with voice source parameters, derived from flow glottograms (FLOGG) that were obtained from inverse filtering the audio signal. Results: On the basis of component analysis, the emotions could be grouped into four “families”, Anger-Contempt, Joy-Love-Pride, Calm-Tender-Neutral and Sad-Fear. Recognition of the intended emotion families by listeners reached accuracy levels far beyond chance level. For the LTAS and FLOGG parameters, vocal loudness had a paramount influence on all. Also after partialing out this factor, some significant correlations were found between FLOGG and LTAS parameters. These parameters could be sorted into groups that were associated with the emotion families. Conclusions: (i) Both LTAS and FLOGG parameters varied significantly with the enactment intentions of the singers. (ii) Some aspects of the voice source are reflected in LTAS parameters. (iii) LTAS parameters affect listener judgment of the enacted emotions and the accuracy of the intended emotional coloring.
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- Sundberg, Johan, et al.
(författare)
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Interdependencies among voice source parameters in emotional speech
- 2011
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Ingår i: IEEE Transactions on Affective Computing. - 1949-3045. ; 2:3, s. 162-174
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Tidskriftsartikel (refereegranskat)abstract
- Emotions have strong effects on the voice production mechanisms and consequently on voice characteristics. The magnitude of these effects, measured using voice source parameters, and the interdependencies among parameters have not been examined. To better understand these relationships, voice characteristics were analyzed in 10 actors' productions of a sustained/a/vowel in five emotions. Twelve acoustic parameters were studied and grouped according to their physiological backgrounds, three related to subglottal pressure, five related to the transglottal airflow waveform derived from inverse filtering the audio signal, and four related to vocal fold vibration. Each emotion appeared to possess a specific combination of acoustic parameters reflecting a specific mixture of physiologic voice control parameters. Features related to subglottal pressure showed strong within-group and between-group correlations, demonstrating the importance of accounting for vocal loudness in voice analyses. Multiple discriminant analysis revealed that a parameter selection that was based, in a principled fashion, on production processes could yield rather satisfactory discrimination outcomes (87.1 percent based on 12 parameters and 78 percent based on three parameters). The results of this study suggest that systems to automatically detect emotions use a hypothesis-driven approach to selecting parameters that directly reflect the physiological parameters underlying voice and speech production.
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| 9. |
- van der Lee, S. J., et al.
(författare)
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A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity
- 2019
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Ingår i: Acta Neuropathologica. - : Springer Science and Business Media LLC. - 0001-6322 .- 1432-0533. ; 138:2, s. 237-250
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Tidskriftsartikel (refereegranskat)abstract
- The genetic variant rs72824905-G (minor allele) in the PLCG2 gene was previously associated with a reduced Alzheimer's disease risk (AD). The role of PLCG2 in immune system signaling suggests it may also protect against other neurodegenerative diseases and possibly associates with longevity. We studied the effect of the rs72824905-G on seven neurodegenerative diseases and longevity, using 53,627 patients, 3,516 long-lived individuals and 149,290 study-matched controls. We replicated the association of rs72824905-G with reduced AD risk and we found an association with reduced risk of dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). We did not find evidence for an effect on Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) risks, despite adequate sample sizes. Conversely, the rs72824905-G allele was associated with increased likelihood of longevity. By-proxy analyses in the UK Biobank supported the associations with both dementia and longevity. Concluding, rs72824905-G has a protective effect against multiple neurodegenerative diseases indicating shared aspects of disease etiology. Our findings merit studying the PLC gamma 2 pathway as drug-target.
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