Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

Isaieva, Karyna; Laprie, Yves; Leclère, Justine; Douros, Ioannis; Felblinger, Jacques; Vuissoz, Pierre‐André

doi:10.1038/s41597-021-01041-3

Cited by 11 publications

(4 citation statements)

References 38 publications

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“…These samples were composed of 500–3216 sagittal slices per run, of which 113–2808 were analysed after discarding time points that were unlikely to be of interest (i.e., retaining time points in which audible sound was produced by the participant as identified by synchronised audio data). These samples covered a range of speech and non-speech behaviours across a range of research disciplines (see Table 1 ), including spoken monosyllables in British English, connected speech in German (Carignan et al, 2020 ), French (Isaieva et al, 2021 ), American English as spoken by a native (L1) speaker (Narayanan et al, 2014 ), and American English spoken by a non-native speaker (Lim et al, 2021 ), as well as non-speech vocal behaviours including vocal size exaggeration (Belyk et al, 2022 ), laughter (Belyk & McGettigan, 2022 ), and whistling (Belyk et al, 2019 ). This sample reflects the natural variation in imaging parameters, and correspondingly in image quality, that analysts may face in practical application (see Fig.…”

Section: Methodsmentioning

confidence: 99%

An open-source toolbox for measuring vocal tract shape from real-time magnetic resonance images

2023

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Real-time magnetic resonance imaging (rtMRI) is a technique that provides high-contrast videographic data of human anatomy in motion. Applied to the vocal tract, it is a powerful method for capturing the dynamics of speech and other vocal behaviours by imaging structures internal to the mouth and throat. These images provide a means of studying the physiological basis for speech, singing, expressions of emotion, and swallowing that are otherwise not accessible for external observation. However, taking quantitative measurements from these images is notoriously difficult. We introduce a signal processing pipeline that produces outlines of the vocal tract from the lips to the larynx as a quantification of the dynamic morphology of the vocal tract. Our approach performs simple tissue classification, but constrained to a researcher-specified region of interest. This combination facilitates feature extraction while retaining the domain-specific expertise of a human analyst. We demonstrate that this pipeline generalises well across datasets covering behaviours such as speech, vocal size exaggeration, laughter, and whistling, as well as producing reliable outcomes across analysts, particularly among users with domain-specific expertise. With this article, we make this pipeline available for immediate use by the research community, and further suggest that it may contribute to the continued development of fully automated methods based on deep learning algorithms.

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Section: Methodsmentioning

confidence: 99%

An open-source toolbox for measuring vocal tract shape from real-time magnetic resonance images

2023

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“…To widen access to real-time speech MRI data and therefore stimulate research in the field, several speech MRI datasets that include series of 2D real-time images of a midsagittal slice of the vocal tract have been made publicly available 3 , 5 – 11 . Most of these datasets include image series of English 5 – 7 or French 8 , 9 speakers performing phonologically comprehensive speech tasks (i.e. speech tasks designed to include most phonemes in a wide range of contexts).…”

Section: Background and Summarymentioning

confidence: 99%

Real-time speech MRI datasets with corresponding articulator ground-truth segmentations

Ruthven,

Peplinski,

Adams

et al. 2023

Sci Data

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The use of real-time magnetic resonance imaging (rt-MRI) of speech is increasing in clinical practice and speech science research. Analysis of such images often requires segmentation of articulators and the vocal tract, and the community is turning to deep-learning-based methods to perform this segmentation. While there are publicly available rt-MRI datasets of speech, these do not include ground-truth (GT) segmentations, a key requirement for the development of deep-learning-based segmentation methods. To begin to address this barrier, this work presents rt-MRI speech datasets of five healthy adult volunteers with corresponding GT segmentations and velopharyngeal closure patterns. The images were acquired using standard clinical MRI scanners, coils and sequences to facilitate acquisition of similar images in other centres. The datasets include manually created GT segmentations of six anatomical features including the tongue, soft palate and vocal tract. In addition, this work makes code and instructions to implement a current state-of-the-art deep-learning-based method to segment rt-MRI speech datasets publicly available, thus providing the community and others with a starting point for developing such methods.

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“…3 Optical microphones are also used during real-time imaging of speech in order to match dynamic images of the vocal tract to sound recordings. [4][5][6] For MR safety applications, specific measurements are often required such as temperature, RF field, electric field, or magnetic field. While modern MRI systems dispose a set of accessory devices, they are usually limited to a narrow bandwidth ECG, a respiratory belt and a finger pulse device.…”

Section: Introductionmentioning

confidence: 99%

“…Other accessory devices, that operate independently of the MR scanner, have been developed for obtaining complementary information about patient motion, such as optical tracking systems, 1 inertial measurement units (including accelerometers, gyroscopes, and possibly magnetometers), 2 or ultrasound devices 3 . Optical microphones are also used during real‐time imaging of speech in order to match dynamic images of the vocal tract to sound recordings 4–6 . For MR safety applications, specific measurements are often required such as temperature, RF field, electric field, or magnetic field.…”

Section: Introductionmentioning

confidence: 99%

A hardware and software system for MRI applications requiring external device data

Isaieva

Fauvel

Weber

et al. 2022

Magnetic Resonance in Med

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Purpose: Numerous MRI applications require data from external devices. Such devices are often independent of the MRI system, so synchronizing these data with the MRI data is often tedious and limited to offline use. In this work, a hardware and software system is proposed for acquiring data from external devices during MR imaging, for use online (in real-time) or offline. Methods:The hardware includes a set of external devices -electrocardiography (ECG) devices, respiration sensors, microphone, electronics of the MR system etc. -using various channels for data transmission (analog, digital, optical fibers), all connected to a server through a universal serial bus (USB) hub. The software is based on a flexible client-server architecture, allowing real-time processing pipelines to be configured and executed. Communication protocols and data formats are proposed, in particular for transferring the external device data to an open-source reconstruction software (Gadgetron), for online image reconstruction using external physiological data. The system performance is evaluated in terms of accuracy of the recorded signals and delays involved in the real-time processing tasks. Its flexibility is shown with various applications. Results:The real-time system had low delays and jitters (on the order of 1 ms). Example MRI applications using external devices included: prospectively gated cardiac cine imaging, multi-modal acquisition of the vocal tract (image, sound, and respiration) and online image reconstruction with nonrigid motion correction. Conclusion:The performance of the system and its versatile architecture make it suitable for a wide range of MRI applications requiring online or offline use of external device data. K E Y W O R D Shardware, physiological data, real-time, signal processing, software Karyna Isaieva and Marc Fauvel contributed equally to this work.

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Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

Cited by 11 publications

References 38 publications

An open-source toolbox for measuring vocal tract shape from real-time magnetic resonance images

An open-source toolbox for measuring vocal tract shape from real-time magnetic resonance images

Real-time speech MRI datasets with corresponding articulator ground-truth segmentations

A hardware and software system for MRI applications requiring external device data

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