Watson Speech: Creating Voice Interfaces Using Speech APIs (W7S168G-SPVC)

Overview

Voice technologies are rapidly reshaping how businesses interact with customers, automate operations, and analyze conversations. Today’s AI systems can deliver fast, accurate, and natural-sounding speech capabilities across multiple languages, supporting use cases such as customer self-service, live agent assistance, real-time analytics, and more.In this course, learners will explore how to apply IBM Watson Speech to Text and Watson Text to Speech to build voice-enabled solutions tailored to their unique business needs.By the end of the course, participants will have the skills to design, customize, and integrate AI-powered voice solutions that deliver seamless, human-like interactions across multiple platforms.

Audience

This course is intended for

  • Anyone looking to automate transcribing and synthesizing speech by using Watson Speech to Text and Text to Speech Technology
  • Practicing AI specialists looking to add speech capabilities to their existing AI-powered services, such as AI assistants and AI agents
  • Practicing Data Scientists looking to get insights from speech and text analysis
  • Business leaders looking to understand the capabilities of Watson Speech to Text and Text to Speech, and apply this technology to solve related domain problems
  • Anyone looking to understand the process of integrating speech-to-text or text-to-speech with an AI assistant or AI agent 

Prerequisites

Before taking this course, you should have:

  • Basic Python
  • Basic knowledge of RESTful API
  • General use of IBM Cloud and an IBM Cloud account

Objective

After completing this course, you should be able to:

  • Explain the value of speech recognition and common Watson Speech business use cases
  • Leverage the Watson Speech to Text API to build a simple working prototype that transcribes speech to text for a business problem
  • Leverage the Watson Text to Speech API to build a simple working prototype that synthesizes text to speech for a business problem
  • Leverage the watsonx.ai API to integrate IBM Granite LLMs for language translation
  • Infuse voice capabilities into an AI assistant built with watsonx Assistant by integrating it with Watson Speech 
Detaylari Göster

Course Outline

  • Unit 1. Introduction to Speech Transcription, Synthesis and the Watson Speech services
  • Unit 2. In-depth exploration of Watson Speech to Text
  • Exercise A: Prepare the Lab Environment for Speech to Text
  • Exercise B: Transcribe with the English US Telephony Model
  • Exercise C: Train a Language Model
  • Exercise D: Using Grammars
  • Exercise E: Language Translation with a Granite LLM
  • Exercise F: Additional Speech to Text Features
  • Unit 3. In-depth exploration of Watson Text to Speech
  • Exercise A: Prepare the Lab Environment for Text to Speech
  • Exercise B: Synthesis Using a Standard English Model
  • Exercise C: Customizing Models
  • Exercise D: Additional Text to Speech Features
  • Unit 4. Adding a Voice Interface with Watson Speech Services
  • Exercise: Integrating watsonx Assistant with Watson Speech
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