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Unlocking Multilingual Magic: Babel Fish with LLM STT TTS

AdvancedGuided Project

Learn how to cross language barriers by building a complete translation system using various AI technologies. First use Speech-to-Text to convert speech to text, then use LLM to intelligently translate between languages (with a focus on comprehension), and finally use Text-to-Speech to convert the translated text back to speech.

Language

  • English

Topic

  • Artificial Intelligence

Enrollment Count

  • 88

Skills You Will Learn

  • Artificial Intelligence, Text-to-Speech, Speech-To-Text, LLM, watsonx

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 90 minutes

Platform

  • SkillsNetwork

Last Update

  • May 11, 2025
About this Guided Project
In today's interconnected world, the ability to communicate across linguistic borders is paramount. As we traverse digital landscapes, working with colleagues, customers, and stakeholders from different corners of the globe, the need for effective and efficient translation tools becomes evident. With the evolution of artificial intelligence, we're not just translating words, but ensuring they're contextually and culturally accurate. This project, capitalizes on the frontier technologies in AI to give learners the skills to build a state-of-the-art translation system. Imagine not only breaking language barriers but also facilitating more empathetic and nuanced interactions across cultures.

👉 Check out the example app you'll create.

A Look at the Project Ahead

By embarking on this journey, you are stepping into the future of translation systems. Here's what lies ahead:
  • Learning Objective 1: Master the integration and application of Watson's Speech-to-Text (STT) to proficiently convert spoken language into written form. 
  • Learning Objective 2: Delve into using watsonx.ai from the API to do translations.
  • Learning Objective 3: Convert written text back to spoken language using Watson Text-To-Speech (TTS). 

What You'll Need

For an optimal experience, use the latest versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Instructors

Bradley Steinfeld

Lover of technology and learning

I work for IBM. I like all tech, especially AI!

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Vicky Kuo

Data Scientist

I believe that success isn't just about individual milestones, but also about uplifting and encouraging others to reach their potential. This is why I'm passionate about combining my technical background with my eagerness to help people overcome technological hurdles and accelerate growth. When I’m not on the job, I love hiking with my two dogs or relaxing in a coffee shop. There's nothing better than having an insightful conversation over coffee, or even better, some volunteer work! Please feel free to reach out to me on LinkedIn.

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Sina Nazeri

Data Scientist at IBM

I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.

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Contributors

Kang Wang

Data Scientist

I am a Data Scientist in the IBM. I am also a PhD Candidate in the University of Waterloo.

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