Musicians Show Improved Speech Segregation in Competitive, Multi-Talker Cocktail Party Scenarios

Abstract

Studies suggest that long-term music experience enhances the brain's ability to segregate speech from noise. Musicians' "speech-in-noise (SIN) benefit" is based largely on perception from simple figure-ground tasks rather than competitive, multitalker scenarios that offer realistic spatial cues for segregation and engage binaural processing. We aimed to investigate whether musicians show perceptual advantages in cocktail party speech segregation in a competitive, multi-talker environment. We used the coordinate response measure (CRM) paradigm to measure speech recognition and localization performance in musicians vs. non-musicians in a simulated 3D cocktail party environment conducted in an anechoic chamber. Speech was delivered through a 16-channel speaker array distributed around the horizontal soundfield surrounding the listener. Participants recalled the color, number, and perceived location of target callsign sentences. We manipulated task difficulty by varying the number of additional maskers presented at other spatial locations in the horizontal soundfield (0-1-2-3-4-6-8 multi-talkers). Musicians obtained faster and better speech recognition amidst up to around eight simultaneous talkers and showed less noise-related decline in performance with increasing interferers than their non-musician peers. Correlations revealed associations between listeners' years of musical training and CRM recognition and working memory. However, better working memory correlated with better speech streaming. Basic (QuickSIN) but not more complex (speech streaming) SIN processing was still predicted by music training after controlling for working memory. Our findings confirm a relationship between musicianship and naturalistic cocktail party speech streaming but also suggest that cognitive factors at least partially drive musicians' SIN advantage.

Physical and Psychoacoustic Characteristics of Typical Noise on Construction Site: “How Does Noise Impact Construction Workers’ Experience?”

“…Based on this, in a noisy environment, speakers often increase the intensity of their voice to ensure the smooth progress of the communication ( Castellanos et al, 1996 ). In addition, related studies have shown that cognitive factors such as working memory (WM) can help the brain better capture target information ( Bidelman and Yoo, 2020 ). According to the results that affect the on-site communications (See Table 5 ), construction workers with a high degree of communications demand believe that post-specific noise has little effect on their communications and hearing.…”

The Listener Effect in Multitalker Speech Segregation and Talker Identification

“…Many factors are likely responsible, and they may be different for different listeners. Those suggested in the literature include variation in the capacity of working memory ( Conway et al, 2001 ; McLaughlin et al, 2018 ; Tamati et al, 2013 ), differences in the ability to selectively attend to targets ( Dai & Shinn-Cunningham, 2016 ; Oberfeld & Klöckner-Nowotny, 2016 ; Ruggles & Shinn-Cunningham, 2011 ; Shinn-Cunningham, 2017), lapses in attention ( Bidelman & Yoo, 2020 ; Brungart & Simpson, 2007 ), variations in hearing sensitivity ( Dewey & Dhar, 2017 ; Lee & Long, 2012 ; Plack et al, 2014 ) and cochlear pathology missed by conventional audiometry ( Bharadwaj et al, 2015 ; Kujawa & Liberman, 2009 ).…”

Performance on stochastic figure-ground perception varies with individual differences in speech-in-noise recognition and working memory capacity

“…In addition to the acoustic properties of the stimulus, interactions among individual difference factors, such as age, working memory capacity (WMC), and musical experience also contribute to differences in auditory perception, stream segregation, and temporal auditory acuity that underlie speech-in-noise recognition. For example, auditory WMC has been positively associated with speech-in-noise recognition (Bidelman & Yoo, 2020;Lad et al, 2020), although this relationship is sometimes not observed in younger adults (e.g., Füllgrabe & Rosen, 2016a, 2016bVermeire et al, 2019) who tend to have better speech-in-noise perception than older adults (Presacco et al, 2016;Vermeire et al, 2019). Although the relationship between WMC and speech-in-noise tasks is sometimes dependent on age, studies investigating musical expertise have found that, for both younger (Bidelman & Yoo, 2020;Parbery-Clark et al, 2009) and older adults (Parbery-Clark et al, 2011), individuals with greater musical experience perform better on auditory WMC and speech-innoise tasks (see Coffey et al, 2017 for a review on musician advantages in SIN tasks).…”

“…Trained musicians can show better auditory stream segregation (Marozeau et al, 2010;Zendel & Alain, 2009), better auditory memory (Parbery-Clark et al, 2011), and greater temporal auditory acuity (Parbery-Clark et al, 2011;Rammsayer & Altenmüller, 2006) than non-musicians. In a study examining speech perception in background noise using a three-dimensional environment, Bidelman and Yoo (2020) found that with an increasing number of distractor speakers, musicians were faster at identifying the target speaker, showed less of a decline in speech recognition, and were better at identifying the location of the target speaker compared to non-musicians. Similarly, musicians performed better on the QSIN compared to non-musicians.…”