Tahlil fyp1.pptx
•Download as PPTX, PDF•
0 likes•9 views
This document provides an overview of a student project that evaluates the performance of log spectrograms and Mel spectrograms for acoustic analysis using deep learning models. The project will extract features from audio datasets using both spectrogram types and test convolutional and recurrent neural networks. Existing systems typically use Mel spectrograms, which apply a mathematical operation to convert frequencies to the Mel scale. The student will analyze which spectrogram performs better for tasks like speech recognition, anomaly detection, and music analysis.
Report
Share
Report
Share
Recommended
Course report-islam-taharimul (1)
This document provides a course report on speech recognition using MATLAB. It includes an abstract, introduction, report outline, design of the system, process and results, flowchart of the experiment, simulation and analysis, discussion, and conclusion sections. The report details using MFCC and GMM algorithms for speech recognition, including signal preprocessing, parameter extraction, and training. Simulation results showed recognition rates approaching 100% for same speakers in quiet environments, but performance was impacted by noise and different speakers. The system demonstrated speech recognition capabilities in MATLAB but had limitations.
Introduction To Applied Machine Learning
This is the first lecture on Applied Machine Learning. The course focuses on the emerging and modern aspects of this subject such as Deep Learning, Recurrent and Recursive Neural Networks (RNN), Long Short Term Memory (LSTM), Convolution Neural Networks (CNN), Hidden Markov Models (HMM). It deals with several application areas such as Natural Language Processing, Image Understanding etc. This presentation provides the landscape.
Anits dip
This document provides an overview of digital image processing (DIP) and discusses various topics related to it. It begins with welcoming remarks and introductions. It then discusses key areas of application for image processing like optical character recognition, security, compression, and medical imaging. Some main techniques covered include image acquisition, pre-processing, enhancement, segmentation, feature extraction, classification, and understanding. Application areas like remote sensing, astronomy, security, and OCR are also summarized. The document provides examples and illustrations of different image processing concepts.
Scalable and Cost-Effective Model-Based Software Verification and Testing
This document describes research on using model-based techniques to generate stress test cases for embedded software. A constraint programming approach is used to model the software system, hardware platform, and performance requirements. The model includes properties of threads, activities, and the scheduling policy. The approach searches for values of tunable parameters, such as delays, that maximize CPU usage while satisfying constraints, in order to evaluate the system under worst-case conditions and help verify that it meets safety standards. The generated test cases effectively stress the system by selecting parameter values that guide the execution towards maximum resource consumption.
System Analysis &DesignDr.Sameer AlimamyFall Semester .docx
System Analysis &Design
Dr.Sameer Alimamy
Fall Semester 2018\2019
Final Project
Cinema Explorer “Mobile Application”
Student named and IDs:
Zahraa AlHashim 201202468
Hanouf AlQannas 201400897
Mashael AlOmair 201001787
Alhanoof AlOtaibi 201201928
Table of Content
1. Executive summary.
1.1 Case Background.
1.2 Organization structure.
1.3 Information system facilities.
1.4 The problem.
2. Scope Definition
Solution
2.1 Request for Information System Services.
2.2 Problem Statement Matrix.
3. Problem Analysis.
3.1 Problems, Opportunities, Objectives and Constraints Matrix.
3.2 Tentative List of Requirements.
4. Modeling Functional Requirements.
4.1 Use Case Glossary.
4.2 Use Case Model Diagram.
4.3 Use Case Narrative.
5. Modeling Object Requirements.
5.1 Entity/Definition Matrix.
5.2 Domain Model.
5.3 ER Diagram.
6. Project Management.
7. Prototype.
8. Appendix A: Preliminary Investigation Interview of Scope Definition.
Appendix B: Interview of Problem Analysis.
1. Executive Summary (200 - 300 words)
1.1 Case Background
According to 2030 vision we create an App that will be the first App for cinema in Saudi Arabia. The cinema App will call Cinema Explorer. We will make a system for the application shows newest movies in many cinemas around Saudi Arabia at different times and places to helps lovers movies booking online. The application will shows to the users the nearest cinemas around them and allows them to select the movies and the seats. In addition, the application has special options for other services, which are selecting 3d glasses, blanket ordering snacks. The payment will be only online by visa and master card distinguished easily to pay. One advantages of the Cinema Explorer Application is save the time instead of going to the Cinema’s places
1.2 Organization Structure:
Cinema Explorer Application
Programmer
AlHanouf Alotaibi
Vice President
Mashael
System Developer
Zahraa
System analyst
Hanouf
1.3 Information System Facilities:
This application will provide up to date movies with the ability to view movie trailers, reserve seats, choose a snack, and pay through this application.
· 4G connection is required for best performance and slow connection may affect the overall app experience
· Find movie by the type of movie, rating, language and cast
· Quick to load and easy to use
1.4 The problem:
Entertainment is a very important aspect in people’s lives. Therefore, people need to have many ways to entertain themselves. One of the most common and popular ways for entertainment is cinema, and there are many cinemas exist globally since 1890s. I addition, since there are many importan.
Audio based Bird Species Recognition
This document presents a project on classifying bird species from audio recordings using hierarchical classification methods. The project retrieved audio data and taxonomy information from an online database. Features were extracted from the audio files and classifiers were trained and tested at different levels of the taxonomy. Both flat classification and hierarchical classification using a local classifier per parent node approach were investigated. The hierarchical classification approach did not significantly improve performance over flat classification. The document provides details on the database, feature extraction methods, classifiers used, and performance evaluation of the different classification approaches.
ICT-GroupProject-Report2-NguyenDangHoa_2
This document is a group project report from the University of Sciences and Technologies of Hanoi that evaluates pitch detection algorithms and their application in musical key detection. The report was produced by a group of 5 students and their supervisor. The report provides an overview of pitch detection algorithms, including YIN estimation, cepstrum analysis, and simplified inverse filter tracking. It also covers musical key detection using pitch class profiles. The report describes the group's research process, implementation of the pitch detection algorithms in Java, and development of an Android application for musical key detection. It presents and discusses the group's results from testing the pitch detection algorithms and evaluating musical key detection.
IRJET- Comparative Analysis of Emotion Recognition System
This document summarizes a research paper that analyzes different machine learning models for speech emotion recognition using the SAVEE dataset. It compares CNN, RFC, XGBoost and SVM classifiers using MFCC features extracted from the audio clips. The CNN model achieved the highest accuracy for emotion recognition when using MFCC features. The paper aims to better understand human emotional states through analyzing dependencies in speech data using these machine learning techniques.
Recommended
Course report-islam-taharimul (1)
This document provides a course report on speech recognition using MATLAB. It includes an abstract, introduction, report outline, design of the system, process and results, flowchart of the experiment, simulation and analysis, discussion, and conclusion sections. The report details using MFCC and GMM algorithms for speech recognition, including signal preprocessing, parameter extraction, and training. Simulation results showed recognition rates approaching 100% for same speakers in quiet environments, but performance was impacted by noise and different speakers. The system demonstrated speech recognition capabilities in MATLAB but had limitations.
Introduction To Applied Machine Learning
This is the first lecture on Applied Machine Learning. The course focuses on the emerging and modern aspects of this subject such as Deep Learning, Recurrent and Recursive Neural Networks (RNN), Long Short Term Memory (LSTM), Convolution Neural Networks (CNN), Hidden Markov Models (HMM). It deals with several application areas such as Natural Language Processing, Image Understanding etc. This presentation provides the landscape.
Anits dip
This document provides an overview of digital image processing (DIP) and discusses various topics related to it. It begins with welcoming remarks and introductions. It then discusses key areas of application for image processing like optical character recognition, security, compression, and medical imaging. Some main techniques covered include image acquisition, pre-processing, enhancement, segmentation, feature extraction, classification, and understanding. Application areas like remote sensing, astronomy, security, and OCR are also summarized. The document provides examples and illustrations of different image processing concepts.
Scalable and Cost-Effective Model-Based Software Verification and Testing
This document describes research on using model-based techniques to generate stress test cases for embedded software. A constraint programming approach is used to model the software system, hardware platform, and performance requirements. The model includes properties of threads, activities, and the scheduling policy. The approach searches for values of tunable parameters, such as delays, that maximize CPU usage while satisfying constraints, in order to evaluate the system under worst-case conditions and help verify that it meets safety standards. The generated test cases effectively stress the system by selecting parameter values that guide the execution towards maximum resource consumption.
System Analysis &DesignDr.Sameer AlimamyFall Semester .docx
System Analysis &Design
Dr.Sameer Alimamy
Fall Semester 2018\2019
Final Project
Cinema Explorer “Mobile Application”
Student named and IDs:
Zahraa AlHashim 201202468
Hanouf AlQannas 201400897
Mashael AlOmair 201001787
Alhanoof AlOtaibi 201201928
Table of Content
1. Executive summary.
1.1 Case Background.
1.2 Organization structure.
1.3 Information system facilities.
1.4 The problem.
2. Scope Definition
Solution
2.1 Request for Information System Services.
2.2 Problem Statement Matrix.
3. Problem Analysis.
3.1 Problems, Opportunities, Objectives and Constraints Matrix.
3.2 Tentative List of Requirements.
4. Modeling Functional Requirements.
4.1 Use Case Glossary.
4.2 Use Case Model Diagram.
4.3 Use Case Narrative.
5. Modeling Object Requirements.
5.1 Entity/Definition Matrix.
5.2 Domain Model.
5.3 ER Diagram.
6. Project Management.
7. Prototype.
8. Appendix A: Preliminary Investigation Interview of Scope Definition.
Appendix B: Interview of Problem Analysis.
1. Executive Summary (200 - 300 words)
1.1 Case Background
According to 2030 vision we create an App that will be the first App for cinema in Saudi Arabia. The cinema App will call Cinema Explorer. We will make a system for the application shows newest movies in many cinemas around Saudi Arabia at different times and places to helps lovers movies booking online. The application will shows to the users the nearest cinemas around them and allows them to select the movies and the seats. In addition, the application has special options for other services, which are selecting 3d glasses, blanket ordering snacks. The payment will be only online by visa and master card distinguished easily to pay. One advantages of the Cinema Explorer Application is save the time instead of going to the Cinema’s places
1.2 Organization Structure:
Cinema Explorer Application
Programmer
AlHanouf Alotaibi
Vice President
Mashael
System Developer
Zahraa
System analyst
Hanouf
1.3 Information System Facilities:
This application will provide up to date movies with the ability to view movie trailers, reserve seats, choose a snack, and pay through this application.
· 4G connection is required for best performance and slow connection may affect the overall app experience
· Find movie by the type of movie, rating, language and cast
· Quick to load and easy to use
1.4 The problem:
Entertainment is a very important aspect in people’s lives. Therefore, people need to have many ways to entertain themselves. One of the most common and popular ways for entertainment is cinema, and there are many cinemas exist globally since 1890s. I addition, since there are many importan.
Audio based Bird Species Recognition
This document presents a project on classifying bird species from audio recordings using hierarchical classification methods. The project retrieved audio data and taxonomy information from an online database. Features were extracted from the audio files and classifiers were trained and tested at different levels of the taxonomy. Both flat classification and hierarchical classification using a local classifier per parent node approach were investigated. The hierarchical classification approach did not significantly improve performance over flat classification. The document provides details on the database, feature extraction methods, classifiers used, and performance evaluation of the different classification approaches.
ICT-GroupProject-Report2-NguyenDangHoa_2
This document is a group project report from the University of Sciences and Technologies of Hanoi that evaluates pitch detection algorithms and their application in musical key detection. The report was produced by a group of 5 students and their supervisor. The report provides an overview of pitch detection algorithms, including YIN estimation, cepstrum analysis, and simplified inverse filter tracking. It also covers musical key detection using pitch class profiles. The report describes the group's research process, implementation of the pitch detection algorithms in Java, and development of an Android application for musical key detection. It presents and discusses the group's results from testing the pitch detection algorithms and evaluating musical key detection.
IRJET- Comparative Analysis of Emotion Recognition System
This document summarizes a research paper that analyzes different machine learning models for speech emotion recognition using the SAVEE dataset. It compares CNN, RFC, XGBoost and SVM classifiers using MFCC features extracted from the audio clips. The CNN model achieved the highest accuracy for emotion recognition when using MFCC features. The paper aims to better understand human emotional states through analyzing dependencies in speech data using these machine learning techniques.
cznamjwyr36wfmgtmdzc-signature-a1b6820cbe628a2a167a0a81f2762fc8f340dd4b93d47a...
The document discusses cognitive radio architecture. It describes 5 perspectives of cognitive radio architecture:
1) Functions, components and design rules
2) The cognition cycle of observe, orient, plan, decide, and act
3) The inference hierarchy from atomic stimuli to context clusters
4) Architecture maps that show behaviors
5) Building cognitive radio architecture on software-defined radio architectures by adding computational intelligence and learning capabilities.
Unit 4 cognitive radio architecture
The document discusses cognitive radio architecture. It describes 5 perspectives of cognitive radio architecture:
1) Functions, components and design rules
2) The cognition cycle of observe, orient, plan, decide, and act
3) The inference hierarchy from atomic stimuli to context clusters
4) Architecture maps that show behaviors
5) Building cognitive radio architecture on software-defined radio architectures by adding computational intelligence and learning capabilities.
Unit1: Introduction to AI
This document provides an overview of an Artificial Intelligence course. The course aims to introduce students to the broad field of AI and prepare them for opportunities in the AI field. It will cover topics like searching, knowledge representation, learning, neural networks, and applications of AI. The course objectives are to provide a basic foundation of concepts in searching and knowledge representation. Students will complete laboratory tasks involving predicate calculus, searching, and neural networks to apply their learning.
Shyam presentation prefinal
This document summarizes a systematic review of empirical evaluations of regression test selection techniques. It identifies 32 techniques that have been evaluated in 38 studies covering 28 papers. The techniques can be classified based on their input, whether they are safe or unsafe, and the type of code or programming paradigm. However, the empirical evidence for differences between techniques is limited, with half of experiments conducted on small programs and few large-scale evaluations. As a result, there is no clear basis for determining a superior technique based on research alone. Future work should aim to better define regression test selection techniques, encourage replications, and standardize reporting of study contexts.
SPECS presentation
The document describes a project by the SPECS Team to perform real-time spectral analysis of large data sets using an FPGA board. The team includes students and faculty from multiple departments who are developing both hardware and software. They are using MATLAB for analysis and algorithm development, Xilinx ISE to design hardware, and an FPGA board for physical implementation. The document provides background on Fourier analysis and how it can decompose signals into frequencies. It also describes the team's work implementing filters and FFT on the FPGA to perform spectral analysis.
machinelearningedgedetectionfaultdetection.pptx
This document summarizes a research paper on using edge machine learning and acoustic emission signals from a smartphone microphone to detect faults in rotating machinery. The researchers developed a two-phase approach: 1) collecting sound data from a drill and preprocessing/extracting features in MATLAB; and 2) deploying a trained machine learning model on an embedded device to classify faults in real-time. Their ensemble bagged decision tree model achieved 96.1% accuracy in detecting five fault classes. While implementation on the edge device reduced accuracy slightly, the approach demonstrated reliability and efficiency for early fault detection to prevent downtime and costs in industrial settings.
Thesis review Presentation
This document summarizes the key elements of a thesis that used ethnographic methods to inform the design of a gamified system for domestic energy conservation. It outlines the background, research focus, methods, findings, contributions, limitations, and further research. The research used telephone interviews and in-home observation to develop player personas, scenarios, and stages of mastery to inform the player focus section of a gamification architecture. The analysis was informed by ethnomethodology. Key findings were that ethnographic data can be used to construct design tools and provide empirical research for gamification. Limitations included a small convenience sample and little prior research in this area.
Artificial Intelligence for Automated Software Testing
This document provides an overview of applying artificial intelligence techniques such as metaheuristic search, machine learning, and natural language processing to problems in automated software testing. It begins with introductions to software testing, relevant AI techniques including genetic algorithms, machine learning, and natural language processing. It then discusses search-based software testing (SBST) as an application of metaheuristic search to problems in test case generation and optimization. Examples are provided of representing test cases as chromosomes for genetic algorithms and defining fitness functions to guide the search for test cases that maximize code coverage.
SEG3101-ch2-3 - ElicitationTechniques.pdf
This document provides an overview of requirements elicitation techniques including analysis of existing systems, documentation, observation, ethnography, interviews, brainstorming, joint application design, prototyping, and use cases. It discusses each technique in 1-2 paragraphs and provides examples of how techniques like ethnography and interviews can be used to understand user needs. The document is intended to teach students about eliciting requirements from stakeholders using various qualitative and quantitative methods.
Dip
This presentation is used in a refresher course at Nuzvid. This is one day session of the course. It introduces research avenues in Image Processing and allied areas to faculty participants..
A Study on the Video Scene Retrieving System
Recently, a variety of video data are being generated, stored, and accessed with advances in computer technology and the Int
ernet.
To make search a video, or a video scene quickly from the data, an efficient and effective technique is needed.
So I proposed a video scene retrieval system based on speech recognition which is using HMM(Hidden Markov Model).
The proposed system is applied to scene retrieval experiments that evaluate a recognition rate for 457 short words.
Experiment result shows average detection accuracy is 68%.
Speaker Identification
Speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. Voice -recognition is combination of the two where it uses learned aspects of a speaker’s voice to determine what is being said - such a system cannot recognize speech from random speakers very accurately, but it can reach high accuracy for individual voices it has been trained with, which gives us various applications in day today life.
Av 738 - Adaptive Filtering Lecture 1 - Introduction
Introductory lecture to Avionics 738 Spring 2018 at Air University PAC Campus by Dr. Bilal A. Siddiqui
Kick-Off Meeting - WP1
The document outlines tasks related to defining requirements for Project SLOPE. Task 1.1 involves identifying user requirements through questionnaires. Task 1.2 defines hardware and equipment needs based on user requirements. Task 1.3 focuses on defining human-machine interfaces for different scenarios like planning, harvesting, and resource management. The tasks involve various partners contributing expertise in areas like 3D modeling, inventory, harvesting, and enterprise resource planning.
Deep learning nowpublishing-vol7-sig-039
This document provides an overview of deep learning methodology and its applications. Deep learning uses multiple levels of nonlinear information processing to learn feature representations from data in either a supervised or unsupervised manner. The document discusses applications of deep learning in areas such as speech recognition, computer vision, natural language processing, and information retrieval, where it has already achieved success or has strong potential to make significant impacts.
Expert system 21 sldes
This document provides an overview of expert systems, including their key components and development process. It defines expert systems as computer systems that emulate the decision-making of human experts in a particular domain. The main components are a knowledge base containing rules and facts, and an inference engine that applies rules to deduce new facts. The development process involves knowledge engineering to extract an expert's knowledge into a formal representation. Rule-based systems represent knowledge through IF-THEN production rules. The document also discusses the advantages and limitations of expert systems.
A Survey of Image Classification with Deep Learning in the Presence of Noisy ...
This document summarizes techniques for image classification in the presence of noisy labels. It discusses two types of noise: feature noise which corrupts data features, and label noise which incorrectly changes a data point's label. Label noise is more harmful to performance. Label noise can occur due to automated labeling systems, multiple experts with varying abilities, or intentionally injected noise. The document then categorizes techniques to address label noise into noise-model based methods, which estimate noise structure, and noise-model free methods, which aim to make classifiers robust without a noise model. Key noise-model based techniques are noisy channel, label cleansing, and sample weighting. Key noise-model free techniques use robust losses, meta-learning, regularizers,
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
B.Tech Project Report
This document discusses a project report submitted for a Bachelor of Technology degree in Electronics and Communication Engineering. It includes an introduction outlining the project overview on real-time speaker recognition, methodology using feature extraction and clustering algorithms, and background on identification including speech production and digital signal processing fundamentals.
Utterance based speaker identification
In this paper we present the implementation of speaker identification system using artificial neural network
with digital signal processing. The system is designed to work with the text-dependent speaker
identification for Bangla Speech. The utterances of speakers are recorded for specific Bangla words using
an audio wave recorder. The speech features are acquired by the digital signal processing technique. The
identification of speaker using frequency domain data is performed using backpropagation algorithm.
Hamming window and Blackman-Harris window are used to investigate better speaker identification
performance. Endpoint detection of speech is developed in order to achieve high accuracy of the system.
How to Add Chatter in the odoo 17 ERP Module
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Aberdeen
More Related Content
Similar to Tahlil fyp1.pptx
cznamjwyr36wfmgtmdzc-signature-a1b6820cbe628a2a167a0a81f2762fc8f340dd4b93d47a...
The document discusses cognitive radio architecture. It describes 5 perspectives of cognitive radio architecture:
1) Functions, components and design rules
2) The cognition cycle of observe, orient, plan, decide, and act
3) The inference hierarchy from atomic stimuli to context clusters
4) Architecture maps that show behaviors
5) Building cognitive radio architecture on software-defined radio architectures by adding computational intelligence and learning capabilities.
Unit 4 cognitive radio architecture
The document discusses cognitive radio architecture. It describes 5 perspectives of cognitive radio architecture:
1) Functions, components and design rules
2) The cognition cycle of observe, orient, plan, decide, and act
3) The inference hierarchy from atomic stimuli to context clusters
4) Architecture maps that show behaviors
5) Building cognitive radio architecture on software-defined radio architectures by adding computational intelligence and learning capabilities.
Unit1: Introduction to AI
This document provides an overview of an Artificial Intelligence course. The course aims to introduce students to the broad field of AI and prepare them for opportunities in the AI field. It will cover topics like searching, knowledge representation, learning, neural networks, and applications of AI. The course objectives are to provide a basic foundation of concepts in searching and knowledge representation. Students will complete laboratory tasks involving predicate calculus, searching, and neural networks to apply their learning.
Shyam presentation prefinal
This document summarizes a systematic review of empirical evaluations of regression test selection techniques. It identifies 32 techniques that have been evaluated in 38 studies covering 28 papers. The techniques can be classified based on their input, whether they are safe or unsafe, and the type of code or programming paradigm. However, the empirical evidence for differences between techniques is limited, with half of experiments conducted on small programs and few large-scale evaluations. As a result, there is no clear basis for determining a superior technique based on research alone. Future work should aim to better define regression test selection techniques, encourage replications, and standardize reporting of study contexts.
SPECS presentation
The document describes a project by the SPECS Team to perform real-time spectral analysis of large data sets using an FPGA board. The team includes students and faculty from multiple departments who are developing both hardware and software. They are using MATLAB for analysis and algorithm development, Xilinx ISE to design hardware, and an FPGA board for physical implementation. The document provides background on Fourier analysis and how it can decompose signals into frequencies. It also describes the team's work implementing filters and FFT on the FPGA to perform spectral analysis.
machinelearningedgedetectionfaultdetection.pptx
This document summarizes a research paper on using edge machine learning and acoustic emission signals from a smartphone microphone to detect faults in rotating machinery. The researchers developed a two-phase approach: 1) collecting sound data from a drill and preprocessing/extracting features in MATLAB; and 2) deploying a trained machine learning model on an embedded device to classify faults in real-time. Their ensemble bagged decision tree model achieved 96.1% accuracy in detecting five fault classes. While implementation on the edge device reduced accuracy slightly, the approach demonstrated reliability and efficiency for early fault detection to prevent downtime and costs in industrial settings.
Thesis review Presentation
This document summarizes the key elements of a thesis that used ethnographic methods to inform the design of a gamified system for domestic energy conservation. It outlines the background, research focus, methods, findings, contributions, limitations, and further research. The research used telephone interviews and in-home observation to develop player personas, scenarios, and stages of mastery to inform the player focus section of a gamification architecture. The analysis was informed by ethnomethodology. Key findings were that ethnographic data can be used to construct design tools and provide empirical research for gamification. Limitations included a small convenience sample and little prior research in this area.
Artificial Intelligence for Automated Software Testing
This document provides an overview of applying artificial intelligence techniques such as metaheuristic search, machine learning, and natural language processing to problems in automated software testing. It begins with introductions to software testing, relevant AI techniques including genetic algorithms, machine learning, and natural language processing. It then discusses search-based software testing (SBST) as an application of metaheuristic search to problems in test case generation and optimization. Examples are provided of representing test cases as chromosomes for genetic algorithms and defining fitness functions to guide the search for test cases that maximize code coverage.
SEG3101-ch2-3 - ElicitationTechniques.pdf
This document provides an overview of requirements elicitation techniques including analysis of existing systems, documentation, observation, ethnography, interviews, brainstorming, joint application design, prototyping, and use cases. It discusses each technique in 1-2 paragraphs and provides examples of how techniques like ethnography and interviews can be used to understand user needs. The document is intended to teach students about eliciting requirements from stakeholders using various qualitative and quantitative methods.
Dip
This presentation is used in a refresher course at Nuzvid. This is one day session of the course. It introduces research avenues in Image Processing and allied areas to faculty participants..
A Study on the Video Scene Retrieving System
Recently, a variety of video data are being generated, stored, and accessed with advances in computer technology and the Int
ernet.
To make search a video, or a video scene quickly from the data, an efficient and effective technique is needed.
So I proposed a video scene retrieval system based on speech recognition which is using HMM(Hidden Markov Model).
The proposed system is applied to scene retrieval experiments that evaluate a recognition rate for 457 short words.
Experiment result shows average detection accuracy is 68%.
Speaker Identification
Speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. Voice -recognition is combination of the two where it uses learned aspects of a speaker’s voice to determine what is being said - such a system cannot recognize speech from random speakers very accurately, but it can reach high accuracy for individual voices it has been trained with, which gives us various applications in day today life.
Av 738 - Adaptive Filtering Lecture 1 - Introduction
Introductory lecture to Avionics 738 Spring 2018 at Air University PAC Campus by Dr. Bilal A. Siddiqui
Kick-Off Meeting - WP1
The document outlines tasks related to defining requirements for Project SLOPE. Task 1.1 involves identifying user requirements through questionnaires. Task 1.2 defines hardware and equipment needs based on user requirements. Task 1.3 focuses on defining human-machine interfaces for different scenarios like planning, harvesting, and resource management. The tasks involve various partners contributing expertise in areas like 3D modeling, inventory, harvesting, and enterprise resource planning.
Deep learning nowpublishing-vol7-sig-039
This document provides an overview of deep learning methodology and its applications. Deep learning uses multiple levels of nonlinear information processing to learn feature representations from data in either a supervised or unsupervised manner. The document discusses applications of deep learning in areas such as speech recognition, computer vision, natural language processing, and information retrieval, where it has already achieved success or has strong potential to make significant impacts.
Expert system 21 sldes
This document provides an overview of expert systems, including their key components and development process. It defines expert systems as computer systems that emulate the decision-making of human experts in a particular domain. The main components are a knowledge base containing rules and facts, and an inference engine that applies rules to deduce new facts. The development process involves knowledge engineering to extract an expert's knowledge into a formal representation. Rule-based systems represent knowledge through IF-THEN production rules. The document also discusses the advantages and limitations of expert systems.
A Survey of Image Classification with Deep Learning in the Presence of Noisy ...
This document summarizes techniques for image classification in the presence of noisy labels. It discusses two types of noise: feature noise which corrupts data features, and label noise which incorrectly changes a data point's label. Label noise is more harmful to performance. Label noise can occur due to automated labeling systems, multiple experts with varying abilities, or intentionally injected noise. The document then categorizes techniques to address label noise into noise-model based methods, which estimate noise structure, and noise-model free methods, which aim to make classifiers robust without a noise model. Key noise-model based techniques are noisy channel, label cleansing, and sample weighting. Key noise-model free techniques use robust losses, meta-learning, regularizers,
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
B.Tech Project Report
This document discusses a project report submitted for a Bachelor of Technology degree in Electronics and Communication Engineering. It includes an introduction outlining the project overview on real-time speaker recognition, methodology using feature extraction and clustering algorithms, and background on identification including speech production and digital signal processing fundamentals.
Utterance based speaker identification
In this paper we present the implementation of speaker identification system using artificial neural network
with digital signal processing. The system is designed to work with the text-dependent speaker
identification for Bangla Speech. The utterances of speakers are recorded for specific Bangla words using
an audio wave recorder. The speech features are acquired by the digital signal processing technique. The
identification of speaker using frequency domain data is performed using backpropagation algorithm.
Hamming window and Blackman-Harris window are used to investigate better speaker identification
performance. Endpoint detection of speech is developed in order to achieve high accuracy of the system.
Similar to Tahlil fyp1.pptx (20)
cznamjwyr36wfmgtmdzc-signature-a1b6820cbe628a2a167a0a81f2762fc8f340dd4b93d47a...
cznamjwyr36wfmgtmdzc-signature-a1b6820cbe628a2a167a0a81f2762fc8f340dd4b93d47a...
Artificial Intelligence for Automated Software Testing
Artificial Intelligence for Automated Software Testing
Av 738 - Adaptive Filtering Lecture 1 - Introduction
Av 738 - Adaptive Filtering Lecture 1 - Introduction
A Survey of Image Classification with Deep Learning in the Presence of Noisy ...
A Survey of Image Classification with Deep Learning in the Presence of Noisy ...
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
Recently uploaded
How to Add Chatter in the odoo 17 ERP Module
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Aberdeen
South African Journal of Science: Writing with integrity workshop (2024)
South African Journal of Science: Writing with integrity workshop (2024)Academy of Science of South Africa
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.How to Manage Your Lost Opportunities in Odoo 17 CRM
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
How to Make a Field Mandatory in Odoo 17
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Your Skill Boost Masterclass: Strategies for Effective Upskilling
Your Skill Boost Masterclass: Strategies for Effective UpskillingExcellence Foundation for South Sudan
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.The History of Stoke Newington Street Names
Presented at the Stoke Newington Literary Festival on 9th June 2024
www.StokeNewingtonHistory.com
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Main Java[All of the Base Concepts}.docx
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Hindi varnamala | hindi alphabet PPT.pdf
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
The Diamonds of 2023-2024 in the IGRA collection
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
PCOS corelations and management through Ayurveda.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
clinical examination of hip joint (1).pdf
described clinical examination all orthopeadic conditions .
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
ANATOMY AND BIOMECHANICS OF HIP JOINT.pdf
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS Template 2023-2024 by: Irene S. Rueco
Recently uploaded (20)
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
South African Journal of Science: Writing with integrity workshop (2024)
South African Journal of Science: Writing with integrity workshop (2024)
How to Manage Your Lost Opportunities in Odoo 17 CRM
How to Manage Your Lost Opportunities in Odoo 17 CRM
Digital Artefact 1 - Tiny Home Environmental Design
Digital Artefact 1 - Tiny Home Environmental Design
Your Skill Boost Masterclass: Strategies for Effective Upskilling
Your Skill Boost Masterclass: Strategies for Effective Upskilling
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
Tahlil fyp1.pptx
- 1. 1
- 2. Evaluation of log spectrogram and Mel spectrogram in acoustic analysis Program: MCS Section: 4rd Student Name: Tahlil Younous Registration No: COSC201301015 Supervisor: Sir Shahab Alam Hashmi Department of Computer Science, Khawaja Fareed UEIT, Rahim Yar Khan. 2
- 3. Agenda • Introduction • Problem statement • Functional requirements • Domain/tools • Feature Extraction • Algorithm • Project Scope • Datasets • Existing System • Methodology Diagram 3
- 4. Introduction • Machine learning and AI is being used extensively in domain of acoustics analysis. • E.g. in speech recognition, voice over, industrial anomaly detection, music generation etc. 4
- 5. Problem Statement For real-time acoustic analysis in deep learning, we use spectrograms for feature extraction, these spectrograms could be of different types e.g. Mel spectrograms and log spectrograms. The aim of this study is to find which type of spectrogram is better then other. 5
- 6. Functional Requirements • Evaluation of performance and accuracy log spectrogram and Mel spectrogram in acoustic analysis using deep learning. • Convolutional models like CNN 1D, CNN 2D and LSTM will be used. • Feature extraction will be done on real-time during execution/model training. 6
- 7. Tools/Domain • Machine learning ,deep learning . • Python library /librosa kapre. 7
- 8. FEATURE EXTRACTION • I used spectrograms for feature extraction. • Mel Spectrogram • Log Spectrogram 8
- 9. Algorithms • Following deep learning models will be utilized in the study. • Convolutional neural network 1.CNN 1D 2.CNN 2D .Recurrent neural network .LSTM 9
- 10. Project Scope • Scope of this project is in automated and intelligent system that take decision on the basis of sounds /acoustics. 10
- 11. Datasets • Cats and dogs sound • Emergency vehicles siren sounds • Music • Urban 8k 11
- 12. Existing system In 1937, Stevens, Volkmann, and Newman proposed a unit of pitch such that equal distances in pitch sounded equally distant to the listener. This is called the Mel scale. We perform a mathematical operation on frequencies to convert them to the Mel scale. https://medium.com/analytics-vidhya/understanding-the- mel-spectrogram-fca2afa2ce53. https://towardsdatascience.com/getting-to-know-the-mel- spectrogram-31bca3e2d9d0 12