Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jul;1(7):075202.
doi: 10.1121/10.0005109. Epub 2021 Jul 9.

Dark tone quality and vocal tract shaping in soprano song production: Insights from real-time MRI

Affiliations

Dark tone quality and vocal tract shaping in soprano song production: Insights from real-time MRI

Elisabeth Lynn et al. JASA Express Lett. 2021 Jul.

Abstract

Tone quality termed "dark" is an aesthetically important property of Western classical voice performance and has been associated with lowered formant frequencies, lowered larynx, and widened pharynx. The present study uses real-time magnetic resonance imaging with synchronous audio recordings to investigate dark tone quality in four professionally trained sopranos with enhanced ecological validity and a relatively complete view of the vocal tract. Findings differ from traditional accounts, indicating that labial narrowing may be the primary driver of dark tone quality across performers, while many other aspects of vocal tract shaping are shown to differ significantly in a performer-specific way.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.
Subject M1 as represented by the mean of all images acquired during her dark (“covered”) aria performance. The six ROIs are superimposed in red, with the selected pixels used to form each region shown as a white “x.” ROIs correspond to labial, coronal, and pharyngeal regions, a region in the larynx immediately superior to the glottis, and regions capturing velum raising and jaw lowering.
Fig. 2.
Fig. 2.
Frequency spectra estimated from audio recordings of subject H5 producing the vowel /a/ in the word “bella.” Spectra from both the dark and non-dark production are shown. Spectra were reconstructed by averaging across windows of a short-time Fourier transform with a 60 ms analysis window, 20% window overlap, Blackman–Harris weighting, and approximately 600 ms total duration. The harmonic structure can be seen, with the spacing between harmonics corresponding to the fundamental frequency (fo), which was ∼357 Hz in both productions. The first two formant frequencies for each production as computed by praat are also indicated. A broad shift in energy toward lower frequencies can be seen when comparing the dark production to the non-dark one, corresponding to the lower formant frequencies in the dark production.
Fig. 3.
Fig. 3.
Mean ROI intensity (M) differences between the dark and non-dark performance conditions, expressed as a proportion of mean ROI intensity during the normal performance condition. Differences are shown for each ROI, representing narrowing of the labial, coronal, pharyngeal, and laryngeal regions of the vocal tract. Individual bars represent subject-specific differences. Negative difference values correspond to lower mean formant frequencies during the dark performance. Higher values for the lips, coronal, pharynx, and larynx regions indicate a more constricted vocal tract in that region. Higher values in the velum and jaw regions represent a more raised velum and jaw, respectively. Asterisks (*) indicate corresponding significant effects, described in Sec. 3, within subjects (below/below bars) and across subjects (curly brackets).
Fig. 4.
Fig. 4.
Mean formant frequency (F) differences between the dark and non-dark performance conditions, expressed as a proportion of mean formant frequencies during the normal performance condition. Differences are shown for each formant, 1–3, with bars representing subject-specific differences. Negative difference values correspond to lower mean formant frequencies during the dark performance. Asterisks (*) indicate corresponding significant effects, described in Sec. 3, within subjects (below bars) and across subjects (curly brackets).

Similar articles

Cited by

References

    1. Alku, P. , Pohjalainen, J. , Vainio, M. , Laukkanen, A. M. , and Story, B. H. (2013). “ Formant frequency estimation of high-pitched vowels using weighted linear prediction,” J. Acoust. Soc. Am. 134(2), 1295–1313.10.1121/1.4812756 - DOI - PubMed
    1. Bloothooft, G. , and Plomp, R. (1986). “ Spectral analysis of sung vowels. III. Characteristics of singers and modes of singing,” J. Acoust. Soc. Am. 79(3), 852–864.10.1121/1.393423 - DOI - PubMed
    1. Boersma, P. (2001). “ Praat: A system for doing phonetics by computer,” Glot. Int. 5, 341–345.
    1. Bresch, E. , and Narayanan, S. S. (2010). “ Real-time MRI investigation of resonance tuning in soprano singing,” J. Acoust. Soc. Am. 128(5), EL335–EL341.10.1121/1.3499700 - DOI - PMC - PubMed
    1. Bresch, E. , Nielsen, J. , Nayak, K. , and Narayanan, S. (2006). “ Synchronized and noise-robust audio recordings during realtime magnetic resonance imaging scans,” J. Acoust. Soc. Am. 120(4), 1791–1794.10.1121/1.2335423 - DOI - PMC - PubMed