Dr Martijn Wieling Workshop

Dr Martijn Wieling Workshop

CLaS-CCD Workshop on analyzing dynamic phonetic data using generalized additive mixed modelling

3 December 2018, Macquarie University

Overview
In the speech sciences, many datasets are encountered which deal with dynamic data collected over time. Examples include diphthongal formant trajectories and articulator trajectories observed using electromagnetic articulography. Traditional approaches for analyzing this type of data generally aggregate data over a certain timespan, or only include measurements at a fixed time point (e.g., formant measurements at the midpoint of a vowel). In this tutorial, I will introduce generalized additive modeling, a non-linear regression method which does not require aggregation or the pre-selection of a fixed time point. Instead, the method is able to identify general patterns over dynamically varying data, while simultaneously accounting for (non-linear) subject and item-related variability. An advantage of this approach is that patterns may be discovered which are hidden when data is aggregated or when a single time point is selected. A corresponding disadvantage is that these analyses are generally more time consuming and complex. This tutorial aims to overcome this disadvantage by providing two lectures and associated hands-on lab sessions on generalized additive modeling applied to articulography data (to illustrate one-dimensional non-linear patterns), and ERP data (to illustrate non-linear interactions of two variables).

Location: Room  3.610, Level 3, Australian Hearing Hub, 16 University Ave, Macquarie University

Learning objectives
After attending this tutorial participants will:
- know the basic concepts underlying generalized additive modeling;
- be able to apply generalized additive modeling to time-series data from the speech sciences

Presenter: Dr Martijn Wieling, University of Groningen, The Netherlands

Program

Participants are also welcome to bring their own data to work on during the lab sessions.

Targeted audience: Introductory/intermediate (some experience with mixed-effects regression is recommended).

Preparation for Attendees: Participants will need to bring their own laptop (with internet access) with the most recent version of R installed, together with the most recent versions of the packages mgcv and itsadug.

All attendees should prepare for participation in the workshop by familiarizing themselves with the tutorial article “Analyzing dynamic phonetic data using generalized additive mixed modeling: A tutorial focusing on articulatory differences between L1 and L2 speakers of English” (Weiling 2018) https://www.sciencedirect.com/science/article/pii/S0095447017301377

In addition, participants are encouraged to bring phonetic data from their own research for analysis in the workshop. Experimental data should be prepared for presentation and analysis in the R environment, using the tools described in the tutorial article.

Resources
http://martijnwieling.nl/files/GAM-tutorial-Wieling.pdf

http://www.let.rug.nl/~wieling/Tutorial/

Registration: To register for the workshop, please email Rosemary.Eliott@mq.edu.au by 28 November 2018.

Enquiries: Rosemary.Eliott@mq.edu.au

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