Gridlines approach for dynamic analysis in speech ultrasound data: A multimodal app

Abstract

Having access to efficient technologies is essential for the accurate description and analysis of articulatory speech patterns. In the area of tongue ultrasound studies, the visualization/analysis processes generally require a solid knowledge of programming languages as well as a deep understanding of articulatory phenomena. This demands the use of a variety of programs for an efficient use of the data collected. In this paper we introduce a multimodal app for visualizing and analyzing tongue contours: UVA—Ultrasound Visualization and Analysis. This app combines the computational power of R and the interactivity of Shiny web apps to allow users to manipulate and explore tongue ultrasound data using cutting-edge methods. One of the greatest strengths of the app is that it has the capability of being modified to adapt to users’ needs. This has potential as an innovative tool for diverse academic and industry audiences.

Techniques and methods for investigating speech articulation: The centrality of instruments

“…This may involve the need to invest more resources in the project, for example, because it often involves having at least two people working on the data collection: one who supervises the instrument and the other who manages data elicitation (Noiray et al, 2020), or because it involves outsourcing the preparation of data for the analysis (Krause et al, 2020). In this sense, developing interfaces that allow the integration of information coming from several sources as proposed for the SOLLAR system discussed by Noiray et al or in the paper on the UVA app presented by Gonzalez (2021) represents an advantage, because such systems allow researchers to simplify and optimize some phases of the data elicitation and analysis process, and thus speed up the work so that more data can be collected and analyzed in the same unit of time.…”