Listen to the Music: We Rely on Musical Genre to Determine Singers’ Accents

Maddy Walter – maddyw37@student.ubc.ca

The University of British Columbia
Department of Linguistics
Vancouver, British Columbia V6T 1Z4
Canada

Additional authors:
Sydney Norris, Sabrina Luk, Marcell Maitinsky, Md Jahurul Islam, and Bryan Gick

Popular version of 3pPP6 – The Role of Genre Association in Sung Dialect Categorization
Presented at the 187th ASA Meeting
Read the abstract at https://eppro01.ativ.me//web/index.php?page=Session&project=ASAFALL24&id=3771321

–The research described in this Acoustics Lay Language Paper may not have yet been peer reviewed–

Have you ever listened to a song and later been surprised to hear the artist speak with a different accent than the one you heard in the song? Take country singer Keith Urban’s song “What About Me” for instance; when listening, you might assume that he has a Southern American (US) English accent. However, in his interviews, he speaks with an Australian English accent. So why did you think he sounded Southern?

Research suggests that specific accents or dialects are associated with musical genres [2], that singers adjust their accents based on genre [4]; and that foreign accents are more difficult to recognize in songs compared to speech [5]. However, when listeners perceive an accent in a song, it is unclear which type of information they rely on: the acoustic speech information or information about the musical genre. Our previous research investigated this question for Country and Reggae music and found that genre recognition may play a larger role in dialect perception than the actual sound of the voice [9].

Our current study explores American Blues and Folk music, genres that allow for easier separation of vocals from instrumentals, with more refined stimuli manipulation. Blues is strongly associated with African American English [3], while Folk can be associated with a variety of (British, American, etc.) dialects [1]. Participants listened to manipulated clips of sung and “spoken” lines taken from songs in both genres, which were transcribed for participants (see Figure 1). AI applications were used to remove instrumentals for both sung and spoken clips, while “spoken” clips also underwent rhythm and pitch normalization so that they sounded like spoken rather than sung speech. After hearing each sung or spoken line, participants were asked to identify the dialect they heard from six options [7, 8] (see Figure 2).

Figure 1: Participant view of a transcript from a Folk song clip.

Figure 2: Participant view of six dialect options after hearing a clip.

Participants were much more confident and accurate in categorizing accents for clips in the Sung condition, regardless of genre. The proportion of uncertainty (“Not Sure” responses) in the Spoken condition was consistent across genres (see “D” in Figure 3), suggesting that participants were more certain of dialect when musical cues were present. Dialect categories followed genre expectations, as can be seen from the increase in identifying African American English for Blues in the Sung condition (see “A”). Removing uncertainty by adding genre cues did not increase the likelihood of “Irish English” or “British English” being chosen for Blues, though it did for Folk (see “B” and “C” in Figure 3), in line with genre-based expectations.

Figure 3: Participant dialect responses.

These findings enhance our understanding of the relationship between musical genre and accent. Referring again to the example of Keith Urban, the singer’s stylistic accent change may not be the only culprit for our interpretation of a Southern drawl. Rather, we may have assumed we were listening to a musician with a Southern American English Accent when we heard the first banjo-like twang or tuned into iHeartCountry Radio. When we listen to a song and perceive a singer’s accent, we are not only listening to the sounds of their speech, but are also shaping our perception from our expectations of dialect based on the musical genre.

References:

1. Carrigan, J., Henry L. (2004). Lornell, kip. the NPR curious listener’s guide to american folk music. Library Journal (1976), 129(19), 63.
2. Coupland, N. (2011). Voice, place and genre in popular song performance. Journal of Sociolinguistics, 15(5), 573–602. https://doi.org/10.1111/j.1467-9841.2011.00514.x.
3. De Timmerman, Romeo, et al. (2024). The globalization of local indexicalities through music: African‐American English and the blues. Journal of Sociolinguistics, 28(1), 3–25. https://doi.org/10.1111/josl.12616.
4. Gibson, A. M. (2019). Sociophonetics of popular music: insights from corpus analysis and speech perception experiments [Doctoral dissertation, University of Canterbury]. http://dx.doi.org/10.26021/4007.
5. Mageau, M., Mekik, C., Sokalski, A., & Toivonen, I. (2019). Detecting foreign accents in song. Phonetica, 76(6), 429–447. https://doi.org/10.1159/000500187.
6. RStudio. (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/.
7. Stoet, G. (2010). PsyToolkit – A software package for programming psychological experiments using Linux. Behavior Research Methods, 42(4), 1096-1104.
8. Stoet, G. (2017). PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments. Teaching of Psychology, 44(1), 24-31.
9. Walter, M., Bengtson, G., Maitinsky, M., Islam, M. J., & Gick, B. (2023). Dialect perception in song versus speech. The Journal of the Acoustical Society of America, 154(4_supplement), A161. https://doi.org/10.1121/10.0023131.