Date of Award


Document Type


Degree Name

Doctor of Philosophy (PhD)


Computer Engineering and Sciences

First Advisor

Veton Z. Këpuska

Second Advisor

Marius C. Silaghi

Third Advisor

Josko Zec

Fourth Advisor

Philip J. Bernhard


It is known that programming languages are textual. We try here to take the advantages of Speech Recognition (SR) and employ them in creating a verbal Language, which takes its instruction from the voice. Because this work is a novel approach in the programming world, we could not find any resources. This dissertation aims to make essential developments in Speech Recognition (SR)and Artificial Intelligence by constructing a new compiler that receives commands verbally and executes them. That means entering data into the Computer by voice commands. This method of input means that we link several major computer topics with several subheadings. For example, there is a significant overlap here between several computer disciplines. The most important fields that we rely on in this topic are Artificial Intelligence applications, especially the distinction of speech by developing a Programming Language that will make a dramatic turning point, perhaps in the concept of programming. Instead of relying on writing, we turn to rely on voice commands. This Compiler can perform many basic operations like any other compilers, but it receives the commands verbally. The instructions are given orally in a spoken language such as English, Arabic, or French. By designing such a Compiler, two main themes emerge: 1) a careful study of the interaction between Artificial Intelligence (AI) and Speech Recognition (SR), and 2) a full understanding of how compilers are constructed and how all operations are driven. This Compiler can be improved by adding a spoken language to the default implementation language, e.g., English. This Compiler can give the user/programmer choices to pick up the preferable spoken language that is supposed to interpret the commands. Moreover, the Compiler gives the programmer a choice to choose the type of output, whether it is textual or conversational (audio), not just sound. Many large companies have developed such Speech Recognition Systems (SRS), especially the companies producing Smartphones, Computers, and Laptops. If the translation is taken as a model application, they have not yet developed the perfect systems. The purpose of this paper is to add facilities to the Speech Recognition (SR) software so that it can deal with spoken languages. It gives application developers more flexibility because they can use their languages in programming verbally rather than textually. Any programming languages can be used to implement such a compiler, starting from "Go" to "Java." Those languages are classified into three main categories based on language-design; Adhoc (PHP and JavaScript as models), Copy&Delete (Java, Go, ...), Copy&Add (C#,for example).


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