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AAI202 Applications of Artificial Intelligence - Torrens University Australia

Assessment - Natural Language Processing and Computer Vision Problem Sets

Learning Outcome 1: Describe the process and components in developing Natural Language Processing and Vision applications.
Learning Outcome 2: Apply development processes and components of Natural Language Processing and Computer Vision to different problems.

Task Summary
In this assessment, you are required to develop an Artificial Intelligence (AI) application that uses computer vision and speech recognition to detect faces and recognise speech. You will then write a report on your application. The report should be written in a clear and concise manner and be no more than 900 words in length (excluding the Appendix). Your report should describe the processes and components in both speech recognition and face detection. You also need to provide evidence of your programming codes in the Appendix to support the testing results. You should also submit the softcopy of your programming source codes together with your report.

Context
Artificial Intelligence (AI) powers speech-based and vision-based systems, helping to enhance multimodal human-computer interaction. Multimodal interaction systems provide the user with more than one mode of interacting with a system. They process two or more combined user input modes, such as speech, facial images, gestures, etc., in a coordinated manner with multimedia system output. For example, a multimodal question answering system employs multiple modalities such as images and text at the input and output level.

In this assessment, you are required to develop a multimodal interaction system which uses computer vision and speech recognition to detect faces and recognise speech. Figure 1 illustrates the block diagram of the multimodal system you are going to develop. The system consists of two paths. The first path is the face detection which is an AI-based technology that can identify and locate the presence of human faces in images or videos. The second path is the speech recognition which is also another AI-based technology that enables the recognition and translation of spoken language into text.

This assessment has three parts:

Part 1 Conduct a study on speech recognition and face detection. Identify the key components in the processes of speech recognition and face detection. You may use the knowledge and skills acquired from Assessment 2 (AI algorithms) to help you to understand some components involving AI algorithms to complete this task.

Part 2 Develop the face detector in the multimodal system using Python programming language. Test the face detector with the images captured by the camera. You are required to test three images with different users in these images.
Note: Some useful resources can be found in the website ("Face Recognition with Python, in Under 25 Lines of Code - Real", n.d.). Example in Python including source codes is given to provide the step-by-step guidelines to assist you. Another example to acquire images from the camera can be found in this link ("Face Detection in Python Using a Webcam - Real Python", n.d.). Please be reminded the images need to be acquired from the camera.

Part 3 Develop the speech recognizer in the multimodal system using Python programming language. Test the speech recognizer with the speech sentences acquired by the microphone. It is recommended you choose short sentences with more than 3 words and less than 10 words. You are required to test at least 3 sentences.

Note: Some useful resources can be found in the website ("Speech Recognition - Learn Python", n.d.). A file called speechRecognizer.zip which can be obtained from the link is also attached. The example in Python including source codes is given to provide the step- by-step guidelines to assist you. Please be reminded the speech needs to be acquired from the microphone.

By completing this assessment item, you will clearly understand the process and components in developing applications in speech recognition and face detection. You will develop the practical skills including programming to develop a multimodal system that consists of speech recogniser and face detector. You will also acquire the presentation skills necessary to present your application and results in your report. This assessment will prepare you to address the problems of speech recognition and computer vision in the real world.

Task Instructions

Your report should include the following:
• A concise ‘Abstract' section;
• An introduction section;
• A section that includes a clear description of the process and key components of speech recognition including a block diagram;
• A section that demonstrates and discusses the testing results on the speech recognizer;
• A section that includes a clear description of the process and key components of face detection including a block diagram;
• A section that demonstrates and discusses the testing results on the face detector; and
• A conclusion that provide a summary of the above work.

Additionally, your final report should:
• be clearly structured (with well-organised content); and
• use the APA referencing style and include a reference list at the end.
For this assessment item, you are required to submit the programming source codes with the final report. Your programming source codes should be:
• written in Python programming language;
• well commented upon in relation to both the main program and each individual module, such as the function module; and
• free of errors, such as compilation errors, runtime errors, etc.

Report Format
The following points are a general guide for the presentation of assessment items: Assessments items should be typed;
• Use 1.5 spacing;
• Use a wide left margin (as markers need space to be able to include their comments);
• Use a standard 12-point font, such as Times New Roman, Calibri or Arial;
• Left-justify body text;
• Number your pages (except for the cover page);
• Insert a header or footer that details your name and student number on each page;
• Always keep a copy (both hard and electronic) of your assessments; and
• Most importantly, always run a spelling and grammar check; however, remember, such checks may not pick up all errors. You should still edit your work manually and carefully.

Referencing
It is essential that you use appropriate APA style for citing and referencing research.

Attachment:- Applications of Artificial Intelligence.rar