Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3065
Full metadata record
DC FieldValueLanguage
dc.contributor.authorNizzad, A.R. M.-
dc.contributor.authorThelijjagoda, S-
dc.date.accessioned2022-11-27T07:07:41Z-
dc.date.available2022-11-27T07:07:41Z-
dc.date.issued2022-10-04-
dc.identifier.citationA. R. M. Nizzad and S. Thelijjagoda, "Designing of a Voice-Based Programming IDE for Source Code Generation: A Machine Learning Approach," 2022 International Research Conference on Smart Computing and Systems Engineering (SCSE), 2022, pp. 14-21, doi: 10.1109/SCSE56529.2022.9905095.en_US
dc.identifier.issn2613-8662-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3065-
dc.description.abstractHumans are precise in recognizing natural languages and responding contextually unlike machines. However, speech recognition or Automatic speech recognition often refers to converting human speech or voice to textual information with the help of artificial intelligence algorithms. With the advancement of Artificial Intelligence technologies and extensive research being conducted in AI, speech recognition has received much attention and has emerged as a subset of Natural Language Processing where the advancement and accuracy in speech recognition will open many ways to provide a high standard of human-computer interaction. In this study, using the pre-trained transformer model with a transfer learning approach, the English to Python dataset was used to train the transformer model to produce syntactically correct source code in python. Additionally, the Word2Vec model was used to generate voice-to-text as input for the model. For the purpose of demonstration, a custom Python IDE is developed to generate source code from voice input. The results and findings suggest that in the transformer model, with the use of transfer learning, any dataset can be trained to produce syntactically correct source code. The model’s training loss and validation loss were below 5 and 2.1, respectively. Future research can focus on generating valid source code from any human spoken language without restricting it to English only.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2022 International Research Conference on Smart Computing and Systems Engineering (SCSE);-
dc.subjectDesigningen_US
dc.subjectVoice-Based Programmingen_US
dc.subjectSource Codeen_US
dc.subjectGenerationen_US
dc.subjectMachine Learningen_US
dc.subjectApproachen_US
dc.titleDesigning of a Voice-Based Programming IDE for Source Code Generation: A Machine Learning Approachen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/SCSE56529.2022.9905095en_US
Appears in Collections:Department of Information Management
Research Papers
Research Papers - Dept of Information of Management

Files in This Item:
File Description SizeFormat 
Designing_of_a_Voice-Based_Programming_IDE_for_Source_Code_Generation_A_Machine_Learning_Approach.pdf
  Until 2050-12-31
1.66 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.