Research – Sociolinguistics Lab

Socio Lab members present (and win!) at MSU’s UURAF

May 14, 2024

Undergraduate students from the MSU Sociolinguistics Lab were well represented at the 2024 University Undergraduate Research and Arts Forum (UURAF) in April. Gage Landeryou and Caroline Zackerman shared research they conducted for their senior theses in Linguistics under the direction of lab co-director Betsy Sneller. Two other lab students, Drake Howard and Lin Cabada, presented on research that they had conducted for faculty supervisors in French and in Writing respectively.

Gage Landeryou gave a winning presentation on transgender speech

Gage Landeryou’s study was titled ExpressING Gender: The effect of situational comfort on (ing) pronunciation in transgender speech. For this innovative work and for an engaging and professional style, Gage was awarded a prize for best oral presentation in the ‘Social Sciences – General’ category.

Gage Landeryou, an undergraduate student in the Sociolinguistics Lab who won first prize with his senior thesis presentation " — Gage Landeryou, one of the two winners for oral presentation in the Social Sciences – General category.

Students interacted with visitors and judges

UURAF is a huge event. It can be really overwhelming for the in-person, on-site student presenters. According to MSU’s UURAF 2024 website:

The 26th UURAF was held onsite at the Breslin Center and online at Symposium. Over 1,000 students from 12 colleges participated in the event. They were mentored by over 600 faculty, staff, post-doctoral fellows, graduate students, and government/industry partners. There were over 700 presentations in 32 different subject areas.

We’re proud to report that Drake, Caroline, and Lin did a great job of explaining their posters to the many visitors and judges who came to see them.

Drake Howard stands in front of his poster and talks to a visitor. — Drake Howard explains his poster to a UURAF 2024 visitor.

Students’ talks and abstracts

Gage Landeryou

ExpressING Gender: The Effect of Situational Comfort on (ING) Pronunciation in Transgender Speech

This study explores sociolinguistic variation in the speech of binary transgender individuals. My main goal is to investigate how a speaker’s comfort with their own gender expression impacts how much they style shift in their pronunciation of (ING) (e.g., pronouncing “running” either as running or runnin’) between queer-friendly settings (like their home) versus public settings. Following the methodology of Gratton (2016), who found nonbinary individuals style shifting between private and public settings to avoid the threat of misgendering, I conducted sociolinguistic interviews with 4 binary trans individuals. Each person was interviewed first in their home, and then in a public and not explicitly queer-friendly environment (like a coffee shop). Interviews were transcribed and time aligned, and auditorily coded for pronunciation of (ING). The primary research question was: do trans speakers use their pronunciation of (ING) in public settings to mitigate the threat of being misgendered, in the same way that the nonbinary speakers in Gratton (2016) do?Presenter(s):

Mentor: Betsy Sneller (Linguistics)

Caroline Zackerman

Canadian Raising and Metalinguistic Awareness in Michigan English

Canadian Raising is a phonological rule by which the /ay/ diphthong raises before voiceless coda consonants (as in the word PRICE) (Chambers 1973). Speakers of Michigan English do exhibit regular Canadian Raising of /ay/; however, they often consider Canadian Raising to be a uniquely Canadian feature and fail to recognize it in their own speech (Niedzielski 1999; Preston 2005). This study investigates the relationship between a speaker of Michigan English’s degree of Canadian Raising and whether or not they report similarities between Canadian English and Michigan English. Tokens of /ay/ are extracted from 8 speakers aged 22 to 40, all born and raised in Michigan. Participants were then asked whether they think that speakers in Michigan sound Canadian. Responses and data are collected from the MI Diaries Project, which collects responses from participants in the MI Diaries project, which sends weekly prompts to over 1,000 diarists, inviting them to self-record their audio responses. As hypothesized, there is a significant relationship between /ay/ height and a speaker’s response to the Canadian question. All speakers exhibit raised /ay/ before voiceless consonants, but this effect is much stronger, resulting in higher /ay/ values, for speakers that reported thinking that Michigan English sounds Canadian. We therefore conclude that awareness of a feature in one’s dialect is correlated with the production of the feature.

Mentor: Betsy Sneller (Linguistics)

Drake Howard and William McLaren

Difficulties in French learning: How can we help?

When learning a second language, many speakers encounter linguistic differences that interfere with or even inhibit their ability to learn this new language. In this study, we explore what specific hurdles and barriers exist for students learning French at the undergraduate level at MSU. The goal of this study is to obtain a better understanding of what particular aspects of the language are perceived by learners as hurdles or difficulties, what teaching and learning strategies are deemed helpful, and what suggestions they can provide to improve the MSU French curriculum and/or their French learning experience. We look at the responses of students in different levels of French (100, 200, 300, 400) who visited the French Learning Center during the spring semester of 2024, and look for commonalities and differences in their self-reported difficulties in various areas of the language, such as pronunciation, spelling, vocabulary, and grammar. We also examine what teaching and learning techniques are the most and least effective according to students, looking to see if there is a pattern or preferred method(s) to better understand and learn French.

Mentor: Anne Violin-Wigent (French)

Lin Cabada, Alyssa Seville, Giovanni Antonio Ramos Loureiro Kizem Rodrigues, Liam Comrie, Brooklyn Bell

Alleviating Homesickness through Magical Practices involving Culture, Heritage, and Family

This project looked at remedies for homesickness through the lenses of varying cultural beliefs, practices, and superstitions with a focus on magical practices. By examining our personal practices, we explored various remedies that people have used for homesickness throughout different regions and historical periods. With this in mind, we researched indigenous literature, religious practices, and the origins of our own practices and beliefs. Using what we found, we executed a piece of original spell work that encompasses the specific historical, magical practices we researched pertaining to homesickness. This was composed through various representations, such as culturally significant deities, symbols and sigils, religious artifacts, and family heirlooms. Our composition is separated into seven categories that represent the movement of the emotional body through the process of remedying homesickness starting with themes of denial, grief, isolation, and ending with acknowledgment, adaptation, and acceptance. Structured as an offering, the final category represents how in order to fully embrace your new life, you must be willing to leave something behind. These components intentionally span across our intersecting identities as students living away from home, relating to our personal experiences with homesickness.

Mentor: David Watson (Writing, Rhetoric, and American Cultures)

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Alumni / Conferences / Events / Faculty / Graduate Students / People / Research

Socio Lab goes to New York City for NWAV 51

October 16, 2023

Adam Barnhardt stands behind a podium. A screen on the wall displays a slide titled "Primary research question." Below are two bullets. The first: "Do early adolescents vary pronunciation of an ongoing sound change when performing age-related stance (child vs teen)? Second: "Previously pursued using small number of speakers in CA looking at GOAT-fronting (Eckert 2011)" — Adam Barnhardt presents “Not all sound changes in progress are used in early-adolescent stance-taking”

Suzanne Wagner and Jack Rechsteiner stand in front of the Wagner, Sneller & Rechsteiner poster at NWAV 51. — Adam Barnhardt presents “Not all sound changes in progress are used in early-adolescent stance-taking”

The MSU Sociolinguistics Lab was well represented at the NWAV 51 conference at Queens College, New York, October 13-15, 2023. We had presentations on some of our first analyses of linguistic data from the MI Diaries project: Dr. Betsy Sneller presented as first author on a talk about Michigan English vowel change in apparent time, and Linguistics PhD students Adam Barnhardt and Yongqing Ye presented their doctoral qualifying paper research on adolescent stance-taking and vowel nasalization respectively. In addition, we had a poster that described our experience of building the MI Diaries ‘brand’ over the last three years. We were pleased to include new first year Second Language Studies student Shannon Harasta, who presented her MA thesis research (Southern Illinois University, Carbondale) on queer individuals’ sense of (dis)comfort with various audiences. And it would not be NWAV without a gathering of MSU Socio Lab alumni and associates, such as Dr. Monica Nesbitt (U Indiana Bloomington), Jack Rechsteiner (U Pittsburgh), Chun-Yi Peng (Borough of Manhattan Community College) and Jayce Garner (Pomona College and MI Diaries NSF-REU 2022).

Read more about the article Socio Lab goes to New York City for NWAV 51

Monica Nesbitt, Suzanne Wagner, Betsy Sneller, Yongqing Ye, Adam Barnhardt, and Shannon Harasta at NWAV 51.

Events / Research

Talk by Dr. Sarah Bunin Benor

September 27, 2023

On October 9th, Dr. Sarah Bunin Benor (Vice Provost and Professor of Contemporary Jewish Studies at Hebrew Union College-Jewish Institute of Religion (LA) and Adjunct Professor in the University of Southern California Linguistics Department) will present a talk titled Beyond bagels and burekas: American Jewish language and identity. The talk will be from 5:30-7:00pm in B-342 Wells Hall. Dr. Benor is hosted by the Michigan State University Jewish Studies program, and her visit is co-sponsored by us, the MSU Sociolinguistics Lab. An abstract of Dr. Benor’s talk is below.

Read more about the article Talk by Dr. Sarah Bunin Benor

Events / Research

Dan Villarreal talk November 3 on auto-coding

September 20, 2022

Dr. Dan Villarreal (University of Pittsburgh) is visiting the Sociolinguistics Lab in early November. He’ll be giving a talk, open to the public, on Thursday November 3, 2022. Dan’s presentation is of special interest to us because it’s about automating analyses of large-scale datasets. As we build a corpus of Michigan speech in the MI Diaries project, we’ve been using automatic speech recognition (ASR) to speed up our transcription time, and working with MSU’s Institute for Cyber-Enabled Research (ICER) to move some of our data processing to their supercomputer.

Dr. Villarreal is also giving a talk to the SoConDi group at University of Michigan on Nov 4th, 2022, 3-4pm. If you are interested in joining that talk, please contact Yongqing Ye (yeyongqi@msu.edu) or Suzanne Wagner (wagnersu@msu.edu) for the Zoom link.

Sociolinguistic auto-coding: Applications and pitfalls

Dan Villareal, University of Pittsburgh

Time: Thursday, Nov 3, 4:30-6:15pm

Location: Wells Hall B342 and on Zoom

Zoom link: https://msu.zoom.us/j/98418360065 Meeting ID: 984 1836 0065 passcode: sociolab.

Researchers in sociophonetics and variationist sociolinguistics have increasingly turned to computational methods to automate time-consuming research tasks such as data extraction (e.g., Fromont & Hay 2012), phonetic alignment (e.g., McAuliffe et al. 2017), and accurate vowel measurement (e.g., Barreda 2021). In this talk, I discuss the advantages and challenges of using sociolinguistic auto-coding (SLAC), a method in which machine learning classifiers assign variants to variable data (Kendall et al. 2021; McLarty, Jones & Hall 2019; Villarreal et al. 2020; Villarreal under review).

Villarreal et al. (2020) trained random forest classifiers of two sociolinguistic variables of New Zealand English, non-prevocalic /r/ (varying between Present vs. Absent) and intervocalic medial /t/ (Voiced vs. Voiceless), using over 4,000 previously hand-coded tokens (per variable). Cross-validation revealed accuracy rates of 84.5% for /r/ and 91.8% for /t/. In addition to binary predictions, these auto-coders calculate classifier probabilities: the likelihood that a given /r/ token was Present, or a /t/ token was Voiced. In a listening experiment in which 11 phonetically trained listeners coded 60 /r/ tokens, we found a significant positive linear relationship between classifier probability and human judgments; this indicates that classifier probability successfully captures listeners’ perception of phonetically gradient rhoticity. Finally, auto-coders can report which features were most important in classification, helping to shed light on acoustically complex variables like /r/. In short, SLAC can be used for at least three specific functions: binary coding, gradient ‘coding’, and feature selection.

Like other machine learning (ML) methods, however, there are inherent concerns about SLAC’s fairness—that is, whether it generates equally valid predictions for different speaker groups (e.g., Koenecke et al. 2020). First, given that there are multiple definitions of ML fairness that are mutually incompatible (Berk et al. 2018; Corbett-Davies et al. 2017; Kleinberg et al. 2017), fairness metrics must be decided upon within individual research domains; I argue for three fairness metrics relevant to the domain of sociolinguistic auto-coding. Second, I re-analyze Villarreal et al.’s (2020) /r/ auto-coder for fairness; I find poor performance on all three fairness metrics, with women’s tokens coded more accurately than men’s (88.8% vs. 81.4%). Third, to remedy these imbalances, I used the same data to test a variety of unfairness-mitigation strategies from the ML fairness literature; I find substantial improvement with respect to fairness, albeit at the expense of predictive performance.

Given these fairness issues, I reconsider SLAC under Markl’s (2022) premise that some speech and language technologies are too inherently flawed to use. I argue that while SLAC does not fit into this category, its potential users and consumers deserve a “warts and all” awareness of its drawbacks. To that end, I close with concrete recommendations for using SLAC in large-scale research projects.

References

Barreda, Santiago. 2021. Fast Track: fast (nearly) automatic formant-tracking using Praat. Linguistics Vanguard 7(1). https://doi.org/10.1515/lingvan-2020-0051.

Fromont, Robert & Jennifer Hay. 2012. LaBB-CAT: An annotation store. Proceedings of Australasian Language Technology Association Workshop 113–117.

Kendall, Tyler, Charlotte Vaughn, Charlie Farrington, Kaylynn Gunter, Jaidan McLean, Chloe Tacata & Shelby Arnson. 2021. Considering performance in the automated and manual coding of sociolinguistic variables: Lessons from variable (ING). Frontiers in Artificial Intelligence 4(43). https://doi.org/10.3389/frai.2021.648543.

Markl, Nina. 2022. Language variation and algorithmic bias: Understanding algorithmic bias in British English automatic speech recognition. In 2022 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’22), 521–534. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3531146.3533117.

McAuliffe, Michael, Michaela Socolof, Sarah Mihuc, Michael Wagner & Morgan Sonderegger. 2017. Montreal Forced Aligner: Trainable text-speech alignment using Kaldi. In.

McLarty, Jason, Taylor Jones & Christopher Hall. 2019. Corpus-based sociophonetic approaches to postvocalic r-lessness in African American Language. American Speech 94. https://doi.org/10.1215/00031283-7362239.

Villarreal, Dan. under review. Sociolinguistic auto-coding has fairness problems too: Measuring and mitigating bias. Linguistics Vanguard.

Villarreal, Dan, Lynn Clark, Jennifer Hay & Kevin Watson. 2020. From categories to gradience: Auto-coding sociophonetic variation with random forests. Laboratory Phonology 11(6). 1–31. https://doi.org/10.5334/labphon.216.

Faculty / People / Research

MI Diaries app gets NEH grant to go open-source

February 17, 2022

NEH Grant to Develop Open-Source Code for Self-Recording Mobile App

We are delighted to announce that Dr. Betsy Sneller, Assistant Professor of Linguistics and co-Director of the Sociolinguistics Lab, was awarded a $99,908 grant from the National Endowment for the Humanities (NEH) Digital Humanities Advancement Grant (DHAG) program. The new project, “Building and Disseminating an App for Ethnographic Remote Audio Recording”, is an innovative extension of the MI Diaries project. The goal is to provide other researchers with a convenient and accessible method of collecting speech data. In order to do that, Dr. Sneller’s team will develop an open-source code that anyone would be able to use to create a self-recording mobile app for their project.

The inspiration for the project came from the successful adaptation of the MI Diaries app for the study of Judaism through cultural arts led by Laura Yares, Assistant Professor of Religious Studies at MSU, who will serve on the advisory council for the DHAG grant. Co-Director of the Sociolinguistics Lab, Dr. Suzanne Evans Wagner, is also a faculty advisor to the project.