Open Access Open Access  Restricted Access Subscription Access

Voice Based Email for Blind

Albin Shaju, Eldho John, Arun Eldhose, Jojil jose, Reenu Renjith

Abstract


The "Voice-Based Email for Blind" system was created to deal with the particular difficulties that people with visual impairments encounter when handling emails, an activity that has historically relied on visual interfaces. A completely hands-free experience is provided by the system's integration of sophisticated Speech-to-Text (STT) and Text-to-Speech (TTS) features, which allow users to compose, read, and navigate emails using voice commands. By doing this, the limitations imposed by conventional assistive technologies such as screen readers that frequently have trouble being effective and usable in intricate email contexts are removed. The framework uses IMEI-based authentication to provide security and privacy. By using the unique device identification for login, this method eliminates the need for password-based solutions, which can be inconvenient and less secure for users with visual impairments. A powerful emergency alarm module is also included in the system, which tracks accelerometer data to identify falls or unexpected movements. When turned on, the system immediately notifies designated emergency contacts in real time, including the user's position, providing a crucial degree of security and assistance for those who rely on it. In addition to increasing the user's sense of security, this feature promotes increased independence by enabling visually impaired people to confidently navigate their surroundings. This all-inclusive framework offers vital safety and security measures that are customized to the needs of visually impaired people in addition to providing them with an accessible and user-friendly email management solution. For the visually impaired community, the system seeks to improve independence, inclusion, and digital engagement by fusing state-of-the-art technologies with a user- centric design philosophy.


Full Text:

PDF

References


Rijwan Khan, Pawan Kumar Sharma, Sumit Raj, Sushil Kr. Verma,Sparsh Katiyar(2020).Voice Based E- Mail System using Artificial Intelligence.International Journal of Engineering and Advanced Technology (IJEAT),2249– 8958,

Sai, C & Thrinethra, Doddipalli & Devi, S. (2023).NonCommercial International (CC BY-NC 4.0) License Voice Based Email System for Blind People. Journal of Electronics and Informatics, 5(2), 226–234.

Smith, J.& Johnson, L. (2021). Smart navigation for visually impaired people using artificial intelligence. IEEE Sensors Journal, 21(15), 12345–12356.

Zope, Nevewani,Teje,& Parveen, N. (2017).Voice based e-mail system for blind people. International Journal of Scientific Research in Computer Science and Engineering, 5(4), 73–75.

Brown & Davis(2022). Zero-shot voice cloning text-to-speech for dysphonia disorder speakers. Proceedings of Interspeech 2022, 1234– 1238.

Lee & Wilson(2023). Child speech synthesis pipeline and fine-tuning. Proceedings of the 25th International ACM SIGACCESS Conference on Computers and Accessibility, 1–10.

Martinez,&Garcia,(2021). TTS-guided training for accent conversion without parallel data. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29(8), 2345–2356.

Wang Y., & Chen X. (2020). EfficientTTS2: Variational end-to-end text-to-speech synthesis and voice conversion. Advances in Neural Information Processing Systems, 33, 12345–12356.

Taylor & Anderson(2022). TIMIT-TTS: A text-to-speech dataset for multimodal synthetic media detection. Proceedings of the 13th International Conference on Language Resources and Evaluation, 4567–4572.

Navitha,Anitha,Pujari,Archanachandrashekar,&Prasad,V(2020). Personal assistant for blind people. International Journal of Advanced Research in Computer Science, 11(Special Issue I), 233–235.


Refbacks

  • There are currently no refbacks.