Paper PublishingDeep Learning for Natural Language Parsing
Objective
In this application we present a deep learning based architecture for a natural language parser, and investigating the qualities of our parser by using a multi-lingual dependency parser using advanced deep learning techniques.
Abstract
Natural language processing problems (such as speech recognition, text-based data mining, and text or speech generation) are becoming increasingly important. Before effectively approaching many of these problems, it is necessary to process the syntactic structures of the sentences. Here, we proposed a model that which can convert the text from the images into the speech. That is, OCR (optical character recognition) is used that which extracts the text from the images and speech is generated from the given text. Using the one of the python module (GTTS) which is an advanced technique that which converts the text into speech. Here a web page is created, where the user can login to the page and enter the text that which is to be converted into speech.
Keywords: Images, OCR, Text to speech, GTTS, NLP
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Block Diagram
Specifications
H/W Configuration:
- Processor : I3/Intel Processor
- Hard Disk : 160GB
- RAM : 8Gb
S/W Configuration:
- Operating System :Windows 7/8/10 .
- Server side Script: HTML, CSS & JS.
- IDE: Pycharm.
- Libraries Used : Numpy, IO, OS, Flask, keras.
- Technology:Python 3.6+.
Learning Outcomes
- Practical exposure to
- Hardware and software tools
- Solution providing for real time problems
- Working with team/individual
- Work on creative ideas
- Testing techniques
- Error correction mechanisms
- What type of technology versions is used?
- Working of Tensor Flow
- Implementation of Deep Learning techniques
- Working of CNN algorithm
- Working of GoogleNet algorithm
- Working on ResNet50
- Working on VGG16 and VGG19
- Working on AlexNet
- Working of Transfer Learning
- Building of model creations
- Scope of project
- Applications of the project
- About Python language
- About Deep Learning Frameworks
- Use of Data Science
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