Face and Speech Recognition - United Kingdom

Face and Speech Recognition

Facial recognition systems identify and verify a person automatically from a digital image or a video. Speech recognition technology recognises and interprets natural language instructions from human voices and processes these instructions.

REASONS TO CHOOSE

Gain specialised skills in face recognition, speech recognition, and computer vision
Delivered by world-class instructors
The most up-to-date technology and techniques
Use artificial intelligence capabilities to learn from user behaviour
Flexible delivery methods to suit learning style

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Face and Speech Recognition

Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

OpenCV with Python Training Course Outline

Module 1: Applying Geometric Transformations to Images

Installing OpenCV-Python
Reading, Displaying, and Saving Images
Colour Spaces in OpenCV
Image Translation
Rotation
Scaling
Affine and Projective Transformations
Image Warping in OpenCV

Module 2: Detecting Edges and Applying Image Filter

2D Convolution
Blurring, Sharpening, and Edge Detection
Erosion and Dilation
Cartooning an Image

Module 3: Image Features Extraction

Keypoints
Detecting the Corners
SIFT (Scale Invariant Feature Transform)
SURF (Speeded-Up Robust Features)
FAST (Features from Accelerated Segmented Test)
BRIEF (Binary Robust Independent Elementary Features)

Module 4: Seam Carving

What is Seam Carving?
Traditional Resizing Vs Seam Carving

Module 5: Detecting Shapes and Segmenting an Image

Shape Matching and Contour Analysis
Approximating a Contour
Censoring a Shape
Image Segmentation

Module 6: Object Recognition

Object Detection Vs Object Recognition
Dense Feature Detector
Visual Dictionary
Support Vector Machines
Detecting and Tracking Body Parts
Machine Learning by an Artificial Neural Network

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Who should attend this OpenCV with Python Training Course?

The OpenCV with Python Training is a comprehensive program designed to provide participants with the knowledge and skills needed to work with the OpenCV library using the Python programming language. The course is useful for the following professionals:

Computer Vision Enthusiasts
Artificial Intelligence and Machine Learning Developers
Software Engineers
Image Processing Specialists
Robotics Engineers
Data Scientists
Application Developers

Prerequisites of the OpenCV with Python Training Course

There are no formal prerequisites for the OpenCV with Python Training. However, a basic understanding of OpenCV and Python can be beneficial.

OpenCV with Python Training Course Overview

OpenCV for Python allows the running of computer vision algorithms in real time using the Python language. This technology allows applications to be integrated into the cloud seamlessly. It is also an appropriate tool for fast prototyping to solve computer vision problems.

This one-day OpenCV with Python Training course provides delegates with an understanding of the concepts of object tracking and object recognition. It also teaches practical skills for image transformation, including applying geometric transformations to images, detecting edges, segmenting an image and applying image filters. Other knowledge taught includes cartooning an image and seam carving.

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What’s included in this OpenCV with Python Training Course

World-class Training Sessions from Experienced Instructors
OpenCV with Python Training Certificate
Digital Delegate Pack

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Duration

Online Instructor-led (2 days)

Classroom (2 days)

Online Self-paced (16 hours)

Face Recognition Training Course Outline

Module 1: Introduction to Face Recognition and Face Detection

What is Face Recognition?
Face Recognition Processing
Analysis in Face Subspaces

Module 2: Overview of Face Detection

Face Detection
Appearance-Based and Learning Based Approaches
Pre-Processing

Module 3: Modelling Facial Shape and Appearance

Statistical Models of Appearance

Statistical Shape Models
Face Shape Variation
Statistical Models of Texture

Module 4: Overview of Parametric Face Modelling and Tracking

Parametric Face Modelling
Model-Based Trackers: First-Frame Models or Statistical Models

Module 5: Illumination Modelling for Face Recognition

Using PCA for Generating Linear Lighting Models
Harmonic Reﬂectances

Module 6: Facial Skin Colour Modelling

Skin Colour Models

Single Images
Image Sequences

Module 7: Face Recognition in Subspaces

Face Space and its Dimensionality
Image Space Versus Face Space
Linear Subspaces
Recognition with Sets

Module 8: Face Tracking and Recognition from Video

Overview of Face Tracking and Recognition from Video
Time Series State Space Model for Recognition

Module 9: Face Recognition Across Pose and Illumination

Introduction to Face Recognition Across Pose and Illumination

Multiview Face Recognition and Face Recognition Across Pose
Illumination Invariant Face Recognition

Module 10: Overview of Morphable Models

Morphable Model for Face Analysis
3D Morphable Model Construction
Image Analysis with a 3D Morphable Model

Module 11: Facial Expression Analysis

Facial Expression Analysis
Basic Structure of Facial Expression Analysis Systems
Face Detection Methods

Module 12: Face Synthesis and Face Databases

Introduction
Face Modelling
Face Relighting
Face Databases

Module 13: Face Recognition Evaluation Methods

Standard Performance Measures
Open-Set Identification
Verification
Closed-Set Identification

Module 14: Neural and Psychological Perspectives on Human Face Recognition

Psychological Aspects of Face Perception and Recognition
Facial Expressions, Movement, and Social Signals
Neural Systems Underlying Face Recognition

Module 15: Face Recognition Applications

Different Applications of Face Recognition

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Who should attend this Face Recognition Training Course?

The Face Recognition Training is a comprehensive program designed to provide participants with the knowledge and skills needed to understand and implement face recognition technology. The course is useful for the following professionals:

Computer Vision Engineers
Software Developers
Security and Surveillance Experts
Application Developers
Biometric System Developers
Application Developers
Privacy and Ethics Advocates

Prerequisites of the Face Recognition Training Course

There are no formal prerequisites for the Face Recognition Training. However, a basic understanding of facial recognition technology can be beneficial.

Face Recognition Training Course Overview

Face recognition is a type of technology used to identify or verify or an individual’s identity by using their face. Face recognition systems can recognise people in pictures, video, or in real-time. This Face Recognition Training course is designed to provide extensive knowledge of the technological workings of face recognition. Delegates will learn about face recognition processing, techniques for face detection and statistical learning methods.

Specific topics covered include how to align facial shape and texture with an input image, as well as illumination modelling for face recognition and facial skin colour modeling. In addition, delegates will learn how to address the problems of face tracking and recognition when working from a video sequence of images.

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What’s included in this Face Recognition Training Course

World-class Training Sessions from Experienced Instructors
Face Recognition Training Certificate
Digital Delegate Pack

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More information

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Duration

Online Instructor-led (1 days)

Classroom (1 days)

Online Self-paced (8 hours)

CMUSphinx Training Outline

Module 1: Introduction to Speech Recognition

Speech Recognition
Working of Speech Recognition
Structure of Speech
Recognition Process
Model Basics

Module 2: Introduction to CMUSphinx Toolkit

PocketSphinx
Sphinxtrain

Module 3: Practices Before Building an Application

Algorithms
Existing Accuracy Results
Resources
Technologies

Module 4: Building an Application

Using Sphinx
Using PocketSphinx

Module 5: Using PocketSphinx on Android

Referencing Libraries
Setting Permissions
Resource Files
Application

Module 6: Building Phonetic Dictionary and Language Model

Introduction to Phonetic Dictionary
Using Existing Dictionaries
Using g2p-seq2seq to Extend the Dictionary
Using Keyword Lists with PocketSphinx
Building a Grammar
Create Statistical Language Model

Module 7: Adapting Default Acoustic Models

Creating an Adaptation Corpus
Adapting an Acoustic Model
Testing Adaptation
Using Model
Troubleshooting

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Who should attend this CMUSphinix Training Course?

The CMUSphinx Training is a comprehensive program designed to provide participants with the knowledge and skills needed to work with the CMUSphinx open-source speech recognition toolkit. The course is useful for the following professionals:

Speech Recognition Developers
Natural Language Processing (NLP) Engineers
Software Developers
Research Scientists
Artificial Intelligence Experts
Application Developers
Machine Learning Developers

Prerequisites of the CMUSphinx Training Course

There are no formal prerequisites for the CMUSphinx Training. However, a basic understanding of speech recognition technology can be beneficial.

CMUSphinx Training Course Overview

CMUSphinx is a collection of speech recognition development libraries and tools that can be linked into speech-enabled applications. This course focuses on Sphinx4, a Java-based large vocabulary speech recognition system, and PocketSphinx, a version designed to run on mobile devices.

This CMUSphinx Training course is designed to provide knowledge of the applications of the CMUSphinx toolkit. Delegates will gain an understanding of how to build an application with Sphinx4 and PocketSphinx, including how to build a phonetic dictionary and language model. The course also looks at acoustic models and how they can be either adapted or developed.

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What’s included in this CMUSphinx Training Course

World-class Training Sessions from Experienced Instructors
CMUSphinx Training Certificate
Digital Delegate Pack

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More information

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Not sure which course to choose?

Speak to a training expert for advice if you are unsure of what course is right for you. Give us a call on 01344203999 or Enquire.

Face and Speech Recognition FAQs

How long does it take to study a Face and Speech Recognition training course?

This depends on the training course you choose. The Face Recognition course takes 2 days, while the CMUSphinx Training and OpenCV with Python courses last 1 day each.

Do you offer training in my area?

We offer Face and Speech Recognition training courses in locations all over the UK, as well as abroad. We make it easy to find a training venue near you!

What does the Face and Speech Recognition training course include?

The Knowledge Academy’s Face and Speech Recognition training courses include the courseware, a certificate, and tuition from an experienced instructor.

Do these training courses have prerequisites?

Prerequisites vary according to the course. Please see each course for details.

What are the best Face and Speech Recognition courses in the United Kingdom?

Please see our Face and Speech Recognition courses available in the United Kingdom

Which is the best training institute/provider of Face and Speech Recognition in the United Kingdom?

The Knowledge Academy is the Leading global training provider for Face and Speech Recognition.

What is the cost/training fees for Face and Speech Recognition in the United Kingdom

The training fees for Face and Speech Recognition in the United Kingdom starts from £1995

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Best price in the industry

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Trusted & Approved

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Many delivery methods

Flexible delivery methods are available depending on your learning style.

High quality resources

Resources are included for a comprehensive learning experience.

"Really good course and well organised. Trainer was great with a sense of humour - his experience allowed a free flowing course, structured to help you gain as much information & relevant experience whilst helping prepare you for the exam"

Joshua Davies, Thames Water