Speakece: raspberry pi based wearable augmentation device for speech disordered individuals using cnn based models and real-time audio speech recognition/ Sean Iverson G. Geronimo, Rica Mae B. Pedemonte, Angelica A. Perez, Edward Miguel M. Saringan, and Paul Patrick W. Villarin.--

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Geronimo, Sean Iverson G [author]

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TextPublication details: Manila: Technological University of the Philippines, 2025.Description: xiii, 132pages: 29cmContent type:

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BTH TK 870 G47 2025

Dissertation note: College Of Engineering.-- Bachelor of science in electronics engineering: Technological University of the Philippines, 2025. Summary: Speech disorders significantly impact an individual’s ability to communicate effectively, often leading to social and emotional challenges. Assistive technologies can bridge this gap, but many existing solutions are expensive, bulky, or lack real-time capabilities. SpeakECE, a wearable augmentation device designed to help individuals with speech impairments communicate more effectively. Built on a Raspberry Pi platform, the system leverages Convolutional Neural Network (CNN), particularly the Whisper OpenAI model for real-time audio speech recognition and processing. By translating impaired speech and converting it into clear, intelligible output, SpeakECE provides a cost-effective, portable, and user-friendly solution. This research study explores the development, implementation, and validation of the device, contributing to accessible and affordable assistive technology innovations.

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Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Bachelor's Thesis COE	TUP Manila Library	Thesis Section-2nd floor	BTH TK 870 G47 2025 (Browse shelf(Opens below))	c.1	Not for loan		BTH0006441

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Bachelor's thesis

College Of Engineering.--
Bachelor of science in electronics engineering: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

Speech disorders significantly impact an individual’s ability to communicate
effectively, often leading to social and emotional challenges. Assistive technologies can
bridge this gap, but many existing solutions are expensive, bulky, or lack real-time
capabilities. SpeakECE, a wearable augmentation device designed to help individuals with
speech impairments communicate more effectively. Built on a Raspberry Pi platform, the
system leverages Convolutional Neural Network (CNN), particularly the Whisper OpenAI
model for real-time audio speech recognition and processing. By translating impaired
speech and converting it into clear, intelligible output, SpeakECE provides a cost-effective,
portable, and user-friendly solution. This research study explores the development,
implementation, and validation of the device, contributing to accessible and affordable
assistive technology innovations.

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