Computational Linguistics - IPA and XSampa

🎓 Welcome to Computational Linguistics - IPA and XSampa!

Embark on a journey into the world of linguistics with our expert instructor, Jose M. Hernandez, as he guides you through the essentials of computational linguistics with a focus on the International Phonetic Alphabet (IPA) and its successor, X-Sampa. This is an indispensable skill set for any aspiring or practicing linguist looking to apply their expertise at leading tech companies like Apple, Amazon, and Appen.

Why Take This Course? 🌟

• Industry Demand: Mastery of IPA and X-Sampa is a key requirement for linguist roles in cutting-edge companies.
• Practical Skills: Learn to use phonetic alphabets to instruct virtual assistants and enhance Speech-to-Text (STT) applications.
• Language Agnosticism: Understand that the principles of IPA can be applied to any language, expanding your linguistic repertoire.

Course Structure:

1. Part I: Introduction to IPA in English and Beyond

   • Dive into the world of phonemes and learn how they are represented in IPA.
   • Explore the nuances of consonants, their types and features.
   • Transition from IPA to X-Sampa, understanding its significance for computers.

2. Part II: Building Your Own IPA to X-Sampa Converter with Python

   • Develop a converter that can switch between IPA and X-Sampa representations.
   • Apply your knowledge by writing a Python script, transforming linguistic data on the fly.
   • Utilize provided resources, including a PDF for theoretical understanding and a Jupyter notebook for practical application.

What You'll Need to Start:

• Basic familiarity with Python (dictionaries and functions are your starting points).
• The ability to look up a word in any language and recognize the IPA symbols associated with it.

Your Learning Path:

1. Introduction to the Course
2. Overview of IPA
3. Features and Types of Consonants
4. Exploring Vowels
5. Converting IPA to X-Sampa
6. Final Project: Creating Your Own Python Converter

Learning Resources:

• A comprehensive PDF attached to Lecture 7 in Section 2 for theoretical knowledge.
• A detailed Jupyter notebook (.ipynb) for the Python converter project, available in Lecture 32 of Section 7.

Ease of Access:

• No prior coding experience is necessary; everything you need to know about Python will be covered in detail within the videos.
• You can use Anaconda or any other code editor like PyCharm to modify and run your Python scripts.

Join Jose M. Hernandez in this enlightening course that will open doors to a new realm of linguistic capabilities and career opportunities. Enroll now to become proficient in computational linguistics, the bridge between human language and machine intelligence! 📚✨