DESIGNING OF A VOICE – BASED PROGRAMMING IDE FOR SOURCE CODE GENERATION
Abstract
Nowadays coding is not a complex thing to do, by
the advancement in technology and AI gives a crucial role in the
easiness to the day to day life of human beings. Traditional type
of coding is complex and not everyone is flexible with that, by
using the voice coding we can make coding easier. Here we are
integrating the gpt model to find the required code they asked
for, this is done with the help of Natural Language Processing
and Speech Recognition. We are integrating python libraries
with the open AI model gpt 3.5 to get the answers in response to
the speech input that is given by the user. Python libraries are
used for these functions : converting audio to text format and
searching the text in the gpt model and response that is given by
the model.
Keywords:
deep learning, natural language processing, source code generation, voice to source code, voice-based IDPublished
Issue
Section
License
Copyright (c) 2024 International Journal on Emerging Research Areas

This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Arya Raj S, R Gopika Krishnan, Drishya Das, Rohith R, Jocelyn Ann Joseph, Personality Profiling Using CV Analysis , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Nikita Niteen , Simy Mary Kurian, Exploring Explainable AI, Security and Beyond : A Comprehensive Review , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- R Karthika, Maria Toms, S R Aadrash, P U Prabath, InsightAI: Bridging Natural Language and Data Analytics , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Aniruddha Das, Avisikta Modak, The Carbon footprint of Machine Learning Models , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Arun Robin, Tijo Thomas Titus, Ms. Minu Cherian, Improved Handwritten Digit Recognition Using Deep Learning Technique , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Minu Cherian, Elzabeth Bobus, Bala Susan Jacob, M Annapoorna, Ashwin Mathew Zacheria, Empowering Laptop Selection with Natural Language Processing Chatbot and Data Driven Filtering Assistance , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Dipjyoti Deka, Rituparna Seal, Shubham Banik, Unmasking Fraudulent Job Ads: A Critical Review of Machine Learning Techniques for Detecting Fake Jobs , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Muneebah Mohyiddeen, Sana T.H, Anoodh Hussain, Nandana P Narayanan, Sneha Soman, DGCURE: Model for Detection of Dysgraphia , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Betzy Babu Thoppil, Anugrah Premachandran, Annapoorna M, Ashwin Mathew Zachariah, Bala Susan Jacob, Advanced Sensor-Based Landslide and Earthquake Detection and Alert System Utilizing Machine Learning and Computer Vision Technologies , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Krishnendu B, Sreelakshmi A, Sumayya Maheen, Zameel Hassan, Honey Joseph, Chatbot-Enabled Symptom Assessment: Revolutionizing Disease Diagnosis and Patient Care , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
You may also start an advanced similarity search for this article.