Software Bantu Pembuka Aplikasi Pada Dekstop Berbasis Voice Recognition

Akuwan Saleh, Rido Akbar I, Hari Wahjuningrat S

Abstract


The human desire to make it easier to use a tool in order to increase the effectiveness of work production becomes a guide in the world of work. However, physical limitations or physical disabilities, especially the hands, make it difficult for someone to work using these tools. Therefore an assistive software was made to solve these problems, by utilizing the recognition of natural human characteristics using voice or voice recognition. Assistive software opening applications on a computer desktop with voice commands which are then converted into text using processing software with the help of the webscocket and speech-to-text library from Google and the results are processed to open the desired application by the user. In this paper, an application that has been made is able to convert voice to text and can open applications on the desktop so that it makes it easier for users to operate applications on a computer with a system success rate for speech recognition reaching 91.5%.

Keywords


The human desire to make it easier to use a tool in order to increase the effectiveness of work production becomes a guide in the world of work. However, physical limitations or physical disabilities, especially the hands, make it difficult for someone to

Full Text:

PDF

References


Su Myat M, Hia Myo T, "Speech-To-Text Conversion (STT) System Using Hidden Markov Model (HMM)", 2015, International Journal Of Scientific & Technology Research (IJSTR), Vol 4, pp.349-352. June 2015.

Mousmita Sarma, Kandarpa Kumar S, "Acoustic Modeling of Speech Signal using Arti?cial Neural Network", IGI Global, pp. 287-304, June 2015, doi: 10.4018/978-1-4666-8493-5.ch012.

Jianliang Meng, Junwei Zhang and Haoquan Zhao, “Overview of the Speech Recognition Technology”, International Conference on Computational and Information Sciences (ICCIS), pp. 199-202, 2012, doi: 10.1109/ICCIS.2012.202

Sani M .Isa, "Speech Recognition", 2019, https://mti.binus.ac.id/2019/05/08/speech-recognition/ (accessed Jan. 8, 2020).

Manoj Kumar S, Omendri K, "Speech Recognition: A Review", International Journal of Advanced Networking and Applications (IJANA), pp.62-71, 2014

Florian Schulz, “Speech Recognition for Java/Processing”, https://florianschulz.info/stt/ (accessed Jan. 8, 2020).

Soewito, B., Christian, Gunawan, F. E., Diana, & Kusuma, I. G. P, “Websocket to Support Real Time Smart Home Applications”, International Conference on Computer Science and Computational Intelligence (ICCSCI), pp.260-266, September 2019, doi:10.1016/j.procs.2019.09.014




DOI: https://doi.org/10.31284/p.snestik.2021.1690

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Akuwan Saleh

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.