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The Collaboverse: A Collaborative Data-Sharing and Speech Analysis Platform.

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The Collaboverse system bridges gaps in speech-language pathology by unifying digital tools for researchers and clinicians. This platform facilitates collaboration and machine learning applications, narrowing the digital divide.

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Area of Science:

  • Speech-language pathology
  • Computational linguistics
  • Digital health

Background:

  • Digital collaboration in speech-language pathology involves diverse tools, leading to data silos and a digital divide.
  • Bridging gaps between research, clinical practice, and education is crucial for advancing the field.

Purpose of the Study:

  • To introduce Collaboverse, a web-based system designed to unify digital domains in speech-language pathology.
  • To demonstrate Collaboverse's application in common speech-language pathology tasks and machine learning (ML).

Main Methods:

  • Outlines key concepts: digital divide, data management, distributed computing, and ML.
  • Introduces the Collaboverse workspace for researchers, clinicians, and educators.
  • Details an ML approach for prosodic analysis.

Main Results:

  • Collaboverse shows potential in reducing the digital divide within speech-language pathology.
  • The system generates clinically relevant data, particularly for prosody analysis.
  • Includes an augmentative and alternative communication (AAC) app for visual, nontextual communication.

Conclusions:

  • Collaboverse effectively unifies research, clinical, and educational domains in speech-language pathology.
  • The platform facilitates advanced computation and ML applications, addressing prosody analysis challenges.
  • The integrated AAC app enhances communication accessibility.