1
|
Wu D, Jia X, Rao W, Dou W, Li Y, Li B. Construction of a Chinese traditional instrumental music dataset: A validated set of naturalistic affective music excerpts. Behav Res Methods 2024; 56:3757-3778. [PMID: 38702502 PMCID: PMC11133124 DOI: 10.3758/s13428-024-02411-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2024] [Indexed: 05/06/2024]
Abstract
Music is omnipresent among human cultures and moves us both physically and emotionally. The perception of emotions in music is influenced by both psychophysical and cultural factors. Chinese traditional instrumental music differs significantly from Western music in cultural origin and music elements. However, previous studies on music emotion perception are based almost exclusively on Western music. Therefore, the construction of a dataset of Chinese traditional instrumental music is important for exploring the perception of music emotions in the context of Chinese culture. The present dataset included 273 10-second naturalistic music excerpts. We provided rating data for each excerpt on ten variables: familiarity, dimensional emotions (valence and arousal), and discrete emotions (anger, gentleness, happiness, peacefulness, sadness, solemnness, and transcendence). The excerpts were rated by a total of 168 participants on a seven-point Likert scale for the ten variables. Three labels for the excerpts were obtained: familiarity, discrete emotion, and cluster. Our dataset demonstrates good reliability, and we believe it could contribute to cross-cultural studies on emotional responses to music.
Collapse
Affiliation(s)
- Di Wu
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, 311121, China
| | - Xi Jia
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, 311121, China
| | - Wenxin Rao
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
| | - Wenjie Dou
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, 311121, China
| | - Yangping Li
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China
- School of Foreign Studies, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Baoming Li
- Institute of Brain Science and Department of Physiology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, 311121, China.
- Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, 311121, China.
| |
Collapse
|
2
|
Gong B, Li N, Li Q, Yan X, Chen J, Li L, Wu X, Wu C. The Mandarin Chinese auditory emotions stimulus database: A validated set of Chinese pseudo-sentences. Behav Res Methods 2023; 55:1441-1459. [PMID: 35641682 DOI: 10.3758/s13428-022-01868-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/29/2022] [Indexed: 11/08/2022]
Abstract
Emotional prosody is fully embedded in language and can be influenced by the linguistic properties of a specific language. Considering the limitations of existing Chinese auditory stimulus database studies, we developed and validated an emotional auditory stimuli database composed of Chinese pseudo-sentences, recorded by six professional actors in Mandarin Chinese. Emotional expressions included happiness, sadness, anger, fear, disgust, pleasant surprise, and neutrality. All emotional categories were vocalized into two types of sentence patterns, declarative and interrogative. In addition, all emotional pseudo-sentences, except for neutral, were vocalized at two levels of emotional intensity: normal and strong. Each recording was validated with 40 native Chinese listeners in terms of the recognition accuracy of the intended emotion portrayal; finally, 4361 pseudo-sentence stimuli were included in the database. Validation of the database using a forced-choice recognition paradigm revealed high rates of emotional recognition accuracy. The detailed acoustic attributes of vocalization were provided and connected to the emotion recognition rates. This corpus could be a valuable resource for researchers and clinicians to explore the behavioral and neural mechanisms underlying emotion processing of the general population and emotional disturbances in neurological, psychiatric, and developmental disorders. The Mandarin Chinese auditory emotion stimulus database is available at the Open Science Framework ( https://osf.io/sfbm6/?view_only=e22a521e2a7d44c6b3343e11b88f39e3 ).
Collapse
Affiliation(s)
- Bingyan Gong
- School of Nursing, Peking University Health Science Center, Room 510, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Na Li
- Theatre Pedagogy Department, Central Academy of Drama, Beijing, 100710, China
| | - Qiuhong Li
- School of Nursing, Peking University Health Science Center, Room 510, 38 Xueyuan Road, Haidian District, Beijing, 100191, China
| | - Xinyuan Yan
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | - Jing Chen
- Department of Machine Intelligence, Peking University, 5 Yiheyuan Road, Haidian District, Beijing, 100871, China
- Speech and Hearing Research Center, Key Laboratory on Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China
| | - Liang Li
- School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China
| | - Xihong Wu
- Department of Machine Intelligence, Peking University, 5 Yiheyuan Road, Haidian District, Beijing, 100871, China.
- Speech and Hearing Research Center, Key Laboratory on Machine Perception (Ministry of Education), Peking University, Beijing, 100871, China.
| | - Chao Wu
- School of Nursing, Peking University Health Science Center, Room 510, 38 Xueyuan Road, Haidian District, Beijing, 100191, China.
| |
Collapse
|
3
|
Zhang M, Siegle GJ. Linking Affective and Hearing Sciences-Affective Audiology. Trends Hear 2023; 27:23312165231208377. [PMID: 37904515 PMCID: PMC10619363 DOI: 10.1177/23312165231208377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 09/22/2023] [Accepted: 10/01/2023] [Indexed: 11/01/2023] Open
Abstract
A growing number of health-related sciences, including audiology, have increasingly recognized the importance of affective phenomena. However, in audiology, affective phenomena are mostly studied as a consequence of hearing status. This review first addresses anatomical and functional bidirectional connections between auditory and affective systems that support a reciprocal affect-hearing relationship. We then postulate, by focusing on four practical examples (hearing public campaigns, hearing intervention uptake, thorough hearing evaluation, and tinnitus), that some important challenges in audiology are likely affect-related and that potential solutions could be developed by inspiration from affective science advances. We continue by introducing useful resources from affective science that could help audiology professionals learn about the wide range of affective constructs and integrate them into hearing research and clinical practice in structured and applicable ways. Six important considerations for good quality affective audiology research are summarized. We conclude that it is worthwhile and feasible to explore the explanatory power of emotions, feelings, motivations, attitudes, moods, and other affective processes in depth when trying to understand and predict how people with hearing difficulties perceive, react, and adapt to their environment.
Collapse
Affiliation(s)
- Min Zhang
- Shanghai Key Laboratory of Clinical Geriatric Medicine, Huadong Hospital, Fudan University, Shanghai, China
| | - Greg J. Siegle
- Department of Psychiatry, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| |
Collapse
|
4
|
Abstract
Famous musical melodies, such as "Row, Row, Row Your Boat" and "Hot Cross Buns," are frequently used in psychological research. Such melodies have been used to assess the degree of cognitive impairments in various neurological disorders, and to investigate differences between "naming" vs. "knowing." Despite their utility as an experimental stimulus, there is currently no standardized, openly available set of famous musical melodies based on a United States population, as prior work on the topic has primarily relied on creating stimuli in an ad hoc manner. Therefore, the goal of the present work was to create a set of famous musical melodies. Here, we describe the development of the Famous Melodies Stimulus Set, a set of 107 melodies. We provide normative data for the melodies on five dimensions: familiarity, age of acquisition, emotional valence, emotional arousal, and naming ability. Participants (N = 397) rated the melodies on these five variables, validating that most melodies were highly familiar and reliably named. While familiarity ratings were skewed, all other rating scales covered a relatively broad range, allowing for researchers to select melodies for future work based on particular attributes.
Collapse
|