ArticleTrends in hearing
Complex Acoustic Environments: Review, Framework, and Subjective Model.
Article in Trends in hearing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Effects of entropy in real-world noise on speech perception in listeners with normal hearing and hearing lossa).The Journal of the Acoustical Society of America · 2023Article
- Behavioral dynamics of conversation, (mis)communication and coordination in noisy environments.Scientific reports · 2023Article
- Measuring Speech Intelligibility and Hearing-Aid Benefit Using Everyday Conversational Sentences in Real-World Environments.Frontiers in neuroscience · 2022Article
- Binaural detection thresholds and audio quality of speech and music signals in complex acoustic environments.Frontiers in psychology · 2022Article
- Listening Effort in Complex Audiovisual Scenes Under Varying Simulated Room Acoustic Conditions.Trends in hearingArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concept of complex acoustic environments has appeared in several unrelated research areas within acoustics in different variations. Based on a review of the usage and evolution of this concept in the literature, a relevant framework was developed, which includes nine broad characteristics that are thought to drive the complexity of acoustic scenes. The framework was then used to study the most relevant characteristics for stimuli of realistic, everyday, acoustic scenes: multiple sources, source diversity, reverberation, and the listener's task. The effect of these characteristics on perceived scene complexity was then evaluated in an exploratory study that reproduced the same stimuli with a three-dimensional loudspeaker array inside an anechoic chamber. Sixty-five subjects listened to the scenes and for each one had to rate 29 attributes, including complexity, both with and without target speech in the scenes. The data were analyzed using three-way principal component analysis with a (2 3 2) Tucker3 model in the dimensions of scales (or ratings), scenes, and subjects, explaining 42% of variation in the data. "Comfort" and "variability" were the dominant scale components, which span the perceived complexity. Interaction effects were observed, including the additional task of attending to target speech that shifted the complexity rating closer to the comfort scale. Also, speech contained in the background scenes introduced a second subject component, which suggests that some subjects are more distracted than others by background speech when listening to target speech. The results are interpreted in light of the proposed framework.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.