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Generation of Control Logic from Ordinary Speech
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2022 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Developments in automatic code generation are evolving remarkably fast, with companies and researchers competing to reach human-level accuracy and capability. Advancements in this field primarily focus on using machine learning models for end-to-end code generation. This project introduces the system CodeFromVoice, which explores an alternative method for code generation. This method relies on existing Natural Language Processing models combined with traditional parsing methods. CodeFromVoice shows that this approach can generate code from text or transcribed speech using Automatic Speech Recognition. The generated code is limited in complexity and restricted to the context of an existing application but achieves a Word Error Rate of less than 25%.

Abstract [sv]

Utvecklingen av automatisk kodgenerering visar stora framsteg, med företag och forskare som tävlar om att nå mänsklig nivå av noggrannhet och förmåga. Framsteg inom detta område fokuserar främst på användning av maskininlärningsmodeller för hela kodgenerering processen. Detta projekt introducerar systemet CodeFromVoice, som utforskar en alternativ metod för kodgenerering. Denna metod bygger på befintliga NLP-modeller kombinerat med traditionella parsning metoder. CodeFromVoice visar att detta tillvägagångssätt kan generera kod från text eller transkriberat tal med automatisk taligenkänning. Den genererade koden är begränsad i komplexitet och begränsad till sammanhanget av en existerande applikation, men uppnår en ordfelfrekvens som är mindre än 25%.

Place, publisher, year, edition, pages
2022. , p. 61
Keywords [en]
Code generation, generation of code, generation of control logic, natural language processing
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-47347OAI: oai:DiVA.org:hh-47347DiVA, id: diva2:1675799
External cooperation
HMS Networks AB
Subject / course
Computer science and engineering
Educational program
Computer Science and Engineering, 300 credits
Supervisors
Examiners
Available from: 2022-06-05 Created: 2022-06-23 Last updated: 2022-07-07Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf