Aerodynamics and Phonetics of Indigenous Amazonian Speech Sounds

A human figure wearing an oronasal flow mask with pressure transducers. To its right, signal readouts of oral and nasal flow.

Explore how speakers use air flow through the nose and mouth in understudied languages.

Project description

The project aims to describe the uses of nasality, or passage of air through the nose during speech, in Indigenous Amazonian languages. Nearly all languages have nasal consonants such as “m” or “n”; others (such as French) make basic distinctions between nasal and non-nasal vowels. Amazonian languages have an unparalleled level of complexity in how nasality is produced on both consonants and vowels, but have generally not been studied phonetically. They also exhibit "nasal harmony", or spread of nasality from one segment to others across a word. Without understanding “edge cases” such as these, any effort to characterize the general human speech production capacity will not be enough.

Students’ specific role will consist of annotating speech data from Indigenous Amazonian groups which has been recorded by other project team members. The multi-channel data consists of both speech audio and aerodynamic data on airflow through the nose and mouth, which allows for an unprecedented level of precision in determining phonetic details of nasality. However, locating time points of interest in these signals cannot be done without some manual intervention. 

Project outcome

Students will master computational and technical skills both generally useful to careers in data-driven science (file management, basic coding, data visualization) and specifically useful for speech science, linguistics, and speech-related technology (annotation and analysis workflows, phonetic transcription). Students will also gain specific area knowledge in Amazonian languages, speech aerodynamics, and speech acoustics. Finally, students will also be involved in dissemination of work in several scholarly communities of interest (speech science/phonetics, cross-linguistic sound systems, linguistic fieldwork, Amazonian/Indigenous studies). The latter two outcomes will make students highly competitive for further opportunities to study speech science or linguistics. 

Project details

Timing, eligibility and other details
Length of commitment longer than a semester; 6-9 months
Start time Summer (May/June) Project leader will be out of the country until mid-June; project can start at the soonest in late June 2024 and will continue to December 2024. 
  
In-person, remote, or hybrid? Hybrid Project (can be remote and/or in-person; to be determined by mentor and student) 
Level of collaboration Students will work in parallel with each other on similar tasks and may "pool" their labor, but will mostly work independently. 
Benefits Stipend
Who is eligible Any undergraduate student who has completed LIN 431 or CDS 286. Students who will be enrolled in LIN 431 during the project period will also be considered if they earned a B grade or higher in LIN 301.

Core partners

Project mentor

Matthew Faytak

Assistant Professor

Linguistics

Email: faytak@buffalo.edu

Start the project

  1. Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
  2. After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.) 
Start the Digital Badge

Preparation activities

Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase. 

Students will train starting in late June 2024 with the project leader, focusing on use of required software (Praat, which requires a laptop computers running Mac OS or Windows).

Training will also:
● Introduce or augment existing technical/computing skills specific to speech science research (Python, Praat, R, command line interfaces, automatic speech processing utilities, file systems management)
● Guide students through best practices and common workflows for phonetic transcription

Students should also examine a few short project and project-related outputs to give an idea of the project's analytical topics and scope. These include:

Lin & Lapierre 2019, "Articulatory patterns in contrasting nasal-stop sequences in Panãra", UC Berkeley PhonLab report. https://escholarship.org/uc/item/3xp899c0

Rosés Labrada et al. 2023, "Piaroa voiceless stops as partial undergoers of nasal harmony", Proc ICPhS 2023. https://guarant.cz/icphs2023/1005.pdf

Keywords

Language, speech, linguistics, speech science, indigenous languages, phonetics