Voice Assistant System for Construction Quantity Take-off
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Abstract
Quantity take-off is a critical step in determining construction costs, which is an important task in civil engineering. Although the quantity take-off is a repetitive procedure and each iteration has a simple task, quantity take-off is a time-consuming process. The application of artificial intelligence technology will help develop more efficient work systems. The objective of this research is to develop a voice assistant for construction quantity take-off with Python. The three main libraries were used: (1) Speech Recognition 3.8.1, (2) gTTS 2.2.2, and (3) playsound. 1.2.2. The voice input was developed in two types: (1) Information of the building member input one-by-one (2) Data entry by giving all information of the building member one time. The results showed that the program was able to receive the building member information from the sound of speech. Information of the building member input one-by-one gives higher accuracy but takes longer time. The input one-by-one method provides word error rate between 12.36 and 22.45, while all information of the building member one time method provides word error rate between 20.54 and 28.76. The developed program will make the work more comfortable and efficient.
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