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Natural Language Understanding with Python

You're reading from  Natural Language Understanding with Python

Product type Book
Published in Jun 2023
Publisher Packt
ISBN-13 9781804613429
Pages 326 pages
Edition 1st Edition
Languages
Author (1):
Deborah A. Dahl Deborah A. Dahl
Profile icon Deborah A. Dahl

Table of Contents (21) Chapters

Preface Part 1: Getting Started with Natural Language Understanding Technology
Chapter 1: Natural Language Understanding, Related Technologies, and Natural Language Applications Chapter 2: Identifying Practical Natural Language Understanding Problems Part 2:Developing and Testing Natural Language Understanding Systems
Chapter 3: Approaches to Natural Language Understanding – Rule-Based Systems, Machine Learning, and Deep Learning Chapter 4: Selecting Libraries and Tools for Natural Language Understanding Chapter 5: Natural Language Data – Finding and Preparing Data Chapter 6: Exploring and Visualizing Data Chapter 7: Selecting Approaches and Representing Data Chapter 8: Rule-Based Techniques Chapter 9: Machine Learning Part 1 – Statistical Machine Learning Chapter 10: Machine Learning Part 2 – Neural Networks and Deep Learning Techniques Chapter 11: Machine Learning Part 3 – Transformers and Large Language Models Chapter 12: Applying Unsupervised Learning Approaches Chapter 13: How Well Does It Work? – Evaluation Part 3: Systems in Action – Applying Natural Language Understanding at Scale
Chapter 14: What to Do If the System Isn’t Working Chapter 15: Summary and Looking to the Future Index Other Books You May Enjoy

The relationship between conversational AI and NLP

Conversational artificial intelligence is the broad label for an ecosystem of cooperating technologies that enable systems to conduct spoken and text-based conversations with people. These technologies include speech recognition, NLP, dialog management, natural language generation, and text-to-speech generation. It is important to distinguish these technologies, since they are frequently confused. While this book will focus on NLP, we will briefly define the other related technologies so that we can see how they all fit together:

  • Speech recognition: This is also referred to as speech-to-text or automatic speech recognition (ASR). Speech recognition is the technology that starts with spoken audio and converts it to text.
  • NLP: This starts with written language and produces a structured representation that can be processed by a computer. The input written language can either be the result of speech recognition or text that was originally produced in written form. The structured format can be said to express a user’s intent or purpose.
  • Dialog management: This starts with the structured output of NLP and determines how a system should react. System reactions can include such actions as providing information, playing media, or getting more information from a user in order to address their intent.
  • Natural language generation: This is the process of creating textual information that expresses the dialog manager’s feedback to a user in response to their utterance.
  • Text-to-speech: Based on the textural input created by the natural language generation process, the text-to-speech component generates spoken audio output when given text.

The relationships among these components are shown in the following diagram of a complete spoken dialog system. This book focuses on the NLP component. However, because many natural language applications use other components, such as speech recognition, text-to-speech, natural language generation, and dialog management, we will occasionally refer to them:

Figure 1.2 – A complete spoken dialog system

Figure 1.2 – A complete spoken dialog system

In the next two sections, we’ll summarize some important natural language applications. This will give you a taste of the potential of the technologies that will be covered in this book, and it will hopefully get you excited about the results that you can achieve with widely available tools.

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Natural Language Understanding with Python
Published in: Jun 2023 Publisher: Packt ISBN-13: 9781804613429
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