Benjamin Tucker – benjamin.tucker@ualberta.ca
Stephanie Hedges – shedges@ualberta.ca
Department of Linguistics
University of Alberta
Edmonton, Alberta T6G 2E7
Canada

Mark Berardi – mberardi@msu.edu
Eric Hunter – ejhunter@msu.edu
Department of Communicative Sciences and Disorders
Michigan State University
East Lansing, Michigan 48824

Popular version of paper 1aSC3 (your paper version)
Presented Monday morning 11:15 AM – 12:00P PM, December 7, 2020
179^th ASA Meeting, Acoustics Virtually Everywhere

Research into the perception and production of the human voice has shown that the human voice changes with age (e.g., Harnsberger et al., 2008). Most of the previous studies have investigated speech changes over time using groups of people of different ages, while a few studies have tracked how an individual speaker’s voice changes over time. The present study investigates three male speakers and how their voices change over the last 30 to 50 years of their lives.

We used publicly available archives of speeches given to large audiences on a semi-regular basis (generally with a couple of years between each instance). The group of speeches was given during the last 30-50 years of each speaker’s life, meaning that we have samples ranging from the speakers’ late 40s to early 90s. We extracted 5-minute samples (recordings and transcripts) from each speech. We then used the Penn forced-alignment system (this system finds and marks the boundaries of individual speech sounds) to identify word and sound boundaries. Acoustic characteristics of the speech were extracted from the speech signal using a custom script using the Praat software package.

In the present analysis, we investigate changes in the vowel space (the acoustic range of vowels a speaker has produced), fundamental frequency (what a listener hears as pitch), the duration of words and sounds (segments), and speech rate. We model the acoustic characteristics of our speakers using Generalized Additive Models (Hastie & Tibshirani, 1990), which allows for an investigation of non-linear changes over time.

The results are discussed in terms of vocal changes over the lifespan in the speakers’ later-years. Figure 1 illustrates the change in one speaker’s vowel space as he ages. We find that for this speaker the vowel space shifts to lower frequencies as he ages.

Figure 1 – An animation of Speaker 1’s vowel space and how it changes over a period of 50 years. Each colored circle represents a different decade.

We also find a similar effect for fundamental frequency across all three speakers, Figure 2, where the average fundamental frequency of their voices gets lower and lower as they age and then starts to get higher after the age of 70. This effect is the same for word and segment duration. We find that on average as our three speakers age their speech (at least when giving public speeches) gets faster and then slows down after around the age of 70.

Figure 2: Average fundamental frequency of our speakers’ speech as they age.

Figure 3: Average speech rate in syllables per second of our speakers’ speech as they age.

While on average our three speakers show a change in the progression of their speech at the age of 70, each speaker has their own unique speech trajectory. From a physiological standpoint, our data suggest that with age come not only laryngeal changes (changes to the voice) but also a decrease in respiratory health – especially expiratory volume – as has been reflected in previous studies.

Laura L. Koenig – koenig@haskins.yale.edu
Adelphi University
158 Cambridge Avenue
Garden City NY 11530

Susanne Fuchs – fuchs@leibniz-zas.de
Leibniz-Zentrum Allgemeine Sprachwissenschaft (ZAS)
Schützenstr. 18
10117 Berlin (Germany)

Annette Gerstenberg – gerstenberg@uni-potsdam.de
University of Potsdam, Department of Romance Studies
Am Neuen Palais 10
14467 Potsdam (Germany)

Moriah Rastegar – moriahrastegar@mail.adelphi.edu
Adelphi University
158 Cambridge Avenue
Garden City NY 11530

Popular version of the paper: 1aSCb4
Presented: December 7, 2020 at 10:15 AM – 11:00 AM EST

As we age, we change in many ways:  How we look, the way we dress, and how we speak.  Some of these changes are biological, and others are social.  All are potentially informative to those we interact with.

Captions: “Younger (left) and older (right). Image obtained under the publicly-available creative commons licence.  Aging manipulation courtesy of Jolanda Fuchs.”

******

The human voice is a rich source of information on speaker characteristics, and studies indicate that listeners are relatively accurate in judging the age of an unknown person they hear on the phone.  Vocal signals carry information on (a) the sizes of the mouth and throat cavities, which change as we produce different vowels and consonants; (b) the voice pitch, which reflects characteristics of the vocal-folds; and (c) the voice quality, which also reflects vocal-fold characteristics, but in complex and multidimensional ways.  One voice quality dimension is whether a person speaks with a breathier voice quality.  Past studies on the acoustic effects of vocal aging have concentrated on formants, which reflect upper-airway cavity sizes, and fundamental frequency, which corresponds to voice pitch.  Few studies have assessed voice quality.

Further, most past work investigated age by comparing people from different generations.  Cross-generational studies can be confounded by changes in human living conditions such as nutrition, employment settings, and exposure to risk factors.  To separate effects of aging from environmental factors, it is preferable to assess the same individuals at different time points.  Such work is rather rare given the demands of re-connecting with people over long periods of time.

Here, we take advantage of the French LangAge corpus (https://www.uni-potsdam.de/langage/).  Participants engaged in bibliographic interviews beginning in 2005, and were revisited in subsequent years.  Our analysis is based on four women recorded in 2005 and 2015.  We focus on women because biological aging may differ across the sexes. Out of all words, we selected two of the most frequent ones that were produced for each speaker and time point and did not include voiceless sounds.

Numbers 049 and 016 identify the two speakers, f=female, and the following value (e.g. 72) is the age of the speaker.

Our results show that all four speakers have a lower cavity (formant) frequency at older ages.  This may reflect lengthening of the upper airways, e.g. the larynx descends somewhat over time.  Voice quality also changed, with breathier vocal quality at younger ages than at older ages.  However, speakers differed considerably in the magnitude of these changes and in which measures demonstrated aging effects.

In some cultures, a breathy vocal quality is a marker of gender. Lifestyle changes in later life could lead to a reduced need to demonstrate “female” qualities. In our dataset, the speaker with the largest changes in breathiness was widowed between recording times.  Along with physiological factors and social-communicative conditions, ongoing adaptation to gender roles as a person ages may also contribute to changes in voice quality.

Colette Feehan – cmfeehan@iu.edu
Indiana University

Popular version of paper 2pSCb4
Presented Tuesday afternoon, December 8, 2020
179^th ASA meeting, Virtually Everywhere
Click here to read the abstract

Many people do not realize that the “children” they hear in animation are actually voiced by adults¹. There are several reasons for this, including: children cannot work long hours, are difficult to direct, and their voices change as they grow. Using an adult who can simulate a child voice bypasses these issues, but surprisingly not all voice actors (VAs) can create a believable child voice.

Studying what VAs do can tell us about how the vocal tract works. They can speak intelligibly while contorting their mouths in unnatural ways. A few previous studies^2-10 have looked at the acoustics of VAs, or just the sounds that they produce, such as changes in pitch, voice quality (how raspy or breathy a voice sounds), and what kinds of regional dialects they use. This study uses 3D ultrasound and acoustic data from 3 professional and 3 amateur VAs to start answering the question: What do voice actors do with their vocal tracts to sound like a child? There are multiple different strategies to make your vocal tract sound smaller and different actors combine different strategies to make their child-like voices.

Looking at both the acoustics (the sounds they produce) and the ultrasound imaging of their vocal tracts, the strategies identified so far include: Gesture fronting and raising and hyoid bone raising.

Gesture fronting and raising refers to the position of the tongue within the mouth while you speak. If you think about the location of your tongue when repeating “ta ka ta ka…” you will notice that your tongue touches the roof of your mouth in different places to make each of those consonant sounds—farther forward in the mouth for “ta” and farther back for “ka” and the same is true for vowels. Figure 1 comes from analyzing the recording of their speech and shows that the position of the tongue for the adult versus child voice is pretty different for [i] and [ɑ] sounds for this subject. Given this information, we can then look at the ultrasound and see that the tongue positions are indeed farther forward (right) or higher in the mouth for the child voice, see Figure 2

The hyoid bone is a small bone above the larynx in your neck. This bone interrupts the ultrasound signal and prevents an image from showing up, but looking at the location of this hyoid “shadow” can still give us information. If the hyoid shadow is raised and fronted, as seen in Figure 3, it might be the case that the actor is shortening their vocal tract by contracting muscles in their throat.

Figure 4 shows that, for this VA, the hyoid bone shadow was higher throughout the entire utterance while doing a child voice, meaning that the actor might physically shorten the whole vocal tract the whole time while speaking

Data from VAs can help find alternative pronunciations for speech sounds which could help people with speech impediments but could also be used to help trans individuals sound closer to their identity.

References

1. Holliday, C. “Emotion Capture: Vocal Performances by Children in the Computer-Animated Film”. Alphaville: Journal of Film and Screen Media 3 (Summer 2012). Web. ISSN: 2009-4078.
2. Starr, R. L. (2015). Sweet voice: The role of voice quality in a Japanese feminine style. Language in Society, 44(01), 1-34.
3. Teshigawara, M. (2003). Voices in Japanese animation: a phonetic study of vocal stereotypes of heroes and villains in Japanese culture. Dissertation.
4. Teshigawara, M. (2004). Vocally expressed emotions and stereotypes in Japanese animation: Voice qualities of the bad guys compared to those of the good guys. Journal of the Phonetic Society of Japan, 8(1), 60-76.
5. Teshigawara, M., & Murano, E. Z. (2004). Articulatory correlates of voice qualities of good guys and bad guys in Japanese anime: An MRI study. In Proceedings of INTERSPEECH (pp. 1249-1252).
6. Teshigawara, M., Amir, N., Amir, O., Wlosko, E., & Avivi, M. (2007). Effects of random splicing on listeners’ perceptions. In 16th international congress of phonetic sciences (icphs).
7. Teshigawara, M. 2009. Vocal expressions of emotions and personalities in Japanese anime. In Izdebski, K. (ed.), Emotions of the Human Voice, Vol. III Culture and Perception. San Diego: Plural Publishing, 275-287.
8. Teshigawara, K. (2011). Voice-based person perception: two dimensions and their phonetic properties. ICPhSXVII, 1974-1977.
9. Uchida, T. 2007. Effects of F0 range and contours in speech upon the image of speakers’ personality. Proc.19th ICA Madrid. http://www.seaacustica.es/WEB_ICA_07/fchrs/papers/cas-03-024.pdf
10. Lippi-Green, R. (2011). English with an accent : language, ideology and discrimination in the united states. Retrieved from https://ebookcentral.proquest.com