000			03310nam a22003257a 4500
003			OSt
005			20250717142539.0
008			250715b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH TK 870 _bC33 2025
100			_aCabello, Marvin T. _eauthor
245			_aAugmented reality deaf assistance with real-time speech-to-text and text-to-speech translation using raspberry pi-based smart glasses and a mobile application/ _cMarvin T. Cabello, Aeron Joshua F. Dela Cruz, Jhon Jaree F. Genavia, Nathan Miguel G. Icaro, and Dale Joshua S. Ricardo.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_aviii, 124pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Engineering.-- _bBachelor of science in electronics engineering: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aHumans are socially dependent beings. They rely on each other for survival, emotional support, and personal as well as collective growth. To form and nurture these connections, we developed communication – particularly through verbal sounds. The modern world is flooded with different voices from radios, televisions, mobile phones, and other individuals. These voices are necessary tools for learning. However, it is important to acknowledge that not everyone experiences sound in the same manner. Hard of hearing or Deaf individuals perceive communication differently through sign language and lip reading, and with less than 20% of the world population experiencing hearing loss, it is inevitable that there is a gap in communication for hard of hearing individuals and individuals with typical hearing. This study aims to bridge that communication gap by developing an Augmented Reality Glasses with Real-Time Speech-to-Text Translation. The wearable glasses contain a Mini USB Microphone to take the vocal inputs, a Raspberry Pi Zero 2 W microcomputer that uses Google's Speech-to-Text API to process input, an FLCOS micro display that outputs the text and a magnifying glass that enlarges the text to a readable size without obstructing vision. Findings so far have enabled Deaf or hard of hearing individuals to converse in live conversations at an average of <2 seconds transcription delay per word in mostly controlled environments. With less than 20% Word Error Rate (WER) as expected in Google's own API, the system relied on clear and controlled speech to be transcribed properly. Limitations were primarily due to hardware constraints, the Raspberry Pi Zero 2 W's 512MB RAM was a significant performance bottleneck and lack of direct support for higher end input and output devices lowered the performance ceiling. However, this only highlighted the device's pathways for future improvements as technology advances.
650			_aAugmented reality
650			_aDeaf assistance
650			_aSpeech translation
700			_aDela Cruz, Aeron Joshua F. _eauthor
700			_aGenavia, Jhon Jaree F. _eauthor
700			_aIcaro, Nathan Miguel G. _eauthor
700			_aRicardo, Dale Joshua S. _eauthor
942			_2lcc _cBTH COE _n0
999			_c30380 _d30380