Speech Delay Assistive Device for Speech-to-Text Transcription Based on Machine Learning
Despite advances by major companies, existing technologies often misinterpret speech from individuals with speech delays. To address this challenge, a portable machine learning (ML) speech-to-text assistive device was developed for speech-delayed children. The device is composed of a Raspberry Pi 4 and Google Web Speech API and enables the accurate transcription of challenging speech sounds of children aged 6 to 14 years old. The device performs noise reduction and digital transcription. Its performance was validated by speech language pathologists (SLPs). The device achieved 94% word accuracy, 92% sentence accuracy, and a word error rate (WER) of 0 to 14%. The ML-based device is a significant improvement on existing speech therapy tools, offering an accessible solution for speech-delayed children.
Authors
- Maria Kristina C. Rodriguez
- Gheciel Mayce M. Santos (ORCID: https://orcid.org/0009-0000-3276-6076)
- Jennifer C. Dela Cruz (ORCID: https://orcid.org/0000-0001-9461-1467)
Institutions
- Mapúa University (PH)
Publication Details
- Published
- 2025-05-08
- DOI
- https://doi.org/10.3390/engproc2025092060
- Citations
- 1
- Primary Topic
- Educational Technology and Pedagogy
- Type
- article
- Field-Weighted Citation Impact
- 2.48