Abstract
Disruptive effects of background noise on memory have been thoroughly investigated. Potential beneficial context effects of background noise on memory, however, have received far less attention. Here, we explore whether and how unintelligible multiple talker background babbling affects melody recognition. Participants continuously listened to melodies, each of which appeared twice during the experiment. After each melody participants were asked to indicate whether they had heard the melody previously in the experiment. The presence or absence of background noise during first or second melody presentation was manipulated in four conditions (Clear-Clear, Clear-Noise, Noise-Clear, Noise-Noise). We measured recognition performance as well as cumulative disruptive interference between first and second melody presentation. Mixed effects models revealed that recognition in Clear-Clear was significantly better compared to Noise-Clear and Noise-Noise, but not compared to Clear-Noise. Clear-Noise showed descriptively better recognition performance than Noise-Noise, however this comparison did not reach statistical significance. Recognition performance in Clear-Noise was significantly better than in Noise- Clear, suggesting that noise during encoding affects recognition performance more strongly than noise during retrieval. Furthermore, cumulative disruptive interference was stronger in mismatching contexts. Our results suggest that if possible, background noise should be avoided as it negatively affects memory performance. However, if encoding is likely to take place in a noisy environment, then presenting background noise during retrieval may be beneficial. This is because matching background noise during encoding and retrievals appears to reduce cumulative disruptive interference.
Original language | English |
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Pages (from-to) | 96-112 |
Number of pages | 17 |
Journal | Musicae Scientiae |
Volume | 24 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- memory
- musical perception
- noise