Recording and analyzing kinematic data in children and adults with SOLLAR: Sonographic & Optical Linguo-Labial Articulation Recording system

Abstract

Understanding the development of spoken language in young children has become increasingly important for advancing basic theories of language acquisition and for clinical practice. However, such a goal requires refined measurements of speech articulation (e.g., from the tongue), which are difficult to obtain from young children. In recent years though, technological advances have allowed developmental researchers to make significant steps in that direction. For instance, movements of the tongue, an articulator that is essential for spoken language, can now be tracked and recorded in children with ultrasound imaging. This technique has opened novel research avenues in (a)typical language acquisition, enabling researchers to reliably capture what has long remained invisible in the speech of young children. Within this context, we have designed an experimental platform for the recording and the processing of kinematic data: SOLLAR (Sonographic and Optical Linguo-Labial Articulatory Recording system). The method has been tailored for children, but it is suitable for adults. In the present article, we introduce the recording environment developed to record over 100 children and 30 adults within SOLLAR. We then describe SOLLAR's data processing framework, providing examples of data visualization and a summary of strengths and limitations.

Learning to Read Interacts with Children’s Spoken Language Fluency

“…No additional head-to-probe stabilization was employed to maximize the naturalness of speech and make the recording more comfortable for children. Trials during which participants moved were discarded after visual inspection of the data (see Noiray et al, 2020 for a full description of the experimental platform). The acoustic speech signal was simultaneously recorded using a Shure microphone (fps: 48 Hz).…”

Phonological and Articulatory Deficits in the Production of Novel Signs in Children With Developmental Language Disorder

“…A limitation of this work is that much of the critical motion associated with speech targets is not visible and cannot be measured via surface recordings. For example, much of the key motion for speech involves the tongue, which presents measurement challenges, especially in children (but see Noiray et al, 2020 , for examples of recording tongue motion from children). All motions associated with sign are visible on the hands, providing a tractable avenue for exploring cross-modal articulatory deficits in DLD.…”

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

“…First because instrument sensors can disrupt articulation (Rebernik et al, 2021). Then, as often reported, because instruments can condition the posture and positioning of informants and therefore affect their way of speaking, for example by imposing on them unnatural postures in order to safeguard the sensors' ability to capture information of interest, as reported by Krause, Kay, and Kawamoto (2020) and Noiray et al (2020). Lastly, as reported by Noiray et al, instruments can influence the behavior of some particular groups of informants, such as children, to the point that the instrument, or the environment in which the instrument is used, is required to be concealed so as not to be rejected.…”

“…In fact, as reported in all the papers collected here, the discussed instruments and methods for articulatory research require high levels of technical expertise and long phases of training in order to be used successfully. 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.…”