Book Image

Cognitive Computing with IBM Watson

By : Rob High, Tanmay Bakshi
Book Image

Cognitive Computing with IBM Watson

By: Rob High, Tanmay Bakshi

Overview of this book

Cognitive computing is rapidly becoming a part of every aspect of our lives through data science, machine learning (ML), and artificial intelligence (AI). It allows computing systems to learn and keep on improving as the amount of data in the system increases. This book introduces you to a whole new paradigm of computing – a paradigm that is totally different from the conventional computing of the Information Age. You will learn the concepts of ML, deep learning (DL), neural networks, and AI with the help of IBM Watson APIs. This book will help you build your own applications to understand, and solve problems, and analyze them as per your needs. You will explore various domains of cognitive computing, such as NLP, voice processing, computer vision, emotion analytics, and conversational systems. Equipped with the knowledge of machine learning concepts, how computers do their magic, and the applications of these concepts, you’ll be able to research and apply cognitive computing in your projects.
Table of Contents (16 chapters)
Title Page
Copyright and Credits
About Packt

Customizing the speech recognition service

As is the case with virtually all Watson services, you can customize your instance of Watson speech. In this case, the Speech to Text service has two models that can be customized—a language model and an acoustic model—both of which will be explained further.

Customizing Watson's language model

The language model tells Watson about new words to listen out for. In essence, the custom language models expand Watson's vocabulary. You will not provide any acoustic signature for these vocabulary words, but rather you simply create an entry for these words, their display spelling, and its various (one or more) sounds-like phonetic spellings (refer to the Using sounds-like customization section of this chapter).

Watson provides two different ways of adding to its vocabulary. The easier approach is to provide a text document that exemplifies the type of vocabulary that is used in your domain. Watson will parse this document and add any words it does not already...