Assignment Detail:- 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-
Part SummaryIn 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-
ContextArtificial 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-
Part 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 FormatThe 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-
ReferencingIt is essential that you use appropriate APA style for citing and referencing research-
Attachment:- Applications of Artificial Intelligence-rar
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