GE Review: LING 285: Language and Technology
By: Kelsey Cheng ‘25
One of the most nail-biting GEs is GE-E: Physical Science. With one mention, you’re transported back into your high school biology class. Trying to avoid this fate, I took LING 285: Language and Technology as my GE-E. Can I guarantee an easy A? No. But I can guarantee that you’ll learn theory and hard skills that are extremely valuable in the tech industry. If you’re interested in how Alexa and Siri work, read all about it!
About The Class
Ling 285 integrates knowledge from several fields: linguistics, computer science, physics, math, psychology, and biology. The class first starts off with all things linguistics:
How the vocal tract moves to produce language.
The International Phonetic Alphabet, yikes! A lot of students struggled with this, but it just takes time, practice, and making weird noises in the mirror.
How to read sound waves on graphs. It’s interesting to see how classmates’ graphs differed depending on accent and gender.
Then we learn how industry professionals develop computational models of human language used in speech technology.
Use programs like Python and PRAAT to model speech synthesis and recognition. No previous programming skills required! I didn’t have any experience and managed to do well on programming projects.
Ways companies like Amazon and Google use neural networks and machine learning.
This class has a little bit of everything — both theory and hands-on practice! Because it’s so interdisciplinary, it can be challenging to deal with such foreign material.
The Professor
Professor Mary Byram Washburn is straightforward, energetic, and loves her subject area. Be warned, she’s a fast-talker. I often rewatched her lecture recordings. Also, you must come to class to complete pop in-class assignments and fill out missing information on slides. She likes classroom participation and encourages students to visit during office hours if they have any questions. Before any big exam, she dedicates a lecture for review, going over what will be covered and answering questions.
Don’t just take it from me–read what other students had to say:
Read more at Professor Washburn’s ratemyprofessors page (spoiler: she’s rated 4.3/5).
Grading Breakdown
Difficulty Level: 4/5
Most of your grade consists of:
3 technical projects: We work in PRAAT, a software package for speech analysis in phonetics, and later in Python.
Homework: The homework is open-notes, no time limit, and graded on accuracy.
Two midterms and one final: The midterm and final are difficult, but Professor Washburn is clear on what material is covered (no tricky business).
Labs: We review class material and how to use software. The labs were a godsend in cementing what we learned in lecture, so make sure you have a good TA (I had a couple of classmates switch into my TA’s period. Awkward).
There is rarely reading for this class because the subject area is so new and ever changing. All of the information you need are in the slides.
I’m going to be honest, this class is difficult compared to other GE’s. You’re dealing with technology and linguistic terms that you’ve never seen before. I had classmates get Cs on the homework and exams and switch to Pass/No pass. However, getting an A is achievable. I hosted study sessions before every big exam, asked my TA to review wrong homework answers, and practiced problems in the slides. The class’s information builds (i.e. you need to know the linguistics basics to learn about the tech); this can be intimidating, but it also means that you continually relearn material without knowing it.
Also, you’ll do well if you like the material. Seeing Dr. Washburn getting excited about neural networks will rub off on you. This was one of the hardest classes I’ve taken at USC, but it was definitely worth it.
Takeaways
This class is super valuable if you want to work in the tech industry. According to Verified Market Research, the Speech and Voice Recognition Market size was valued at USD 7.5 Billion in 2021. Artificial intelligence, Natural Language Processing, machine learning…put those buzzwords on your resume!
This class started my interest in language and artificial intelligence, so I hope it can have the same impact on others. STEM is daunting, but this class gave me the confidence to explore the field further.
Take This Class If:
You are a linguistics, cognitive science, or computer science major. For Computational Linguistics and Cognitive Science degrees, this class counts for major credit!
You want to learn hard skills like coding in Python.
You prefer hands-on experience to traditional textbook reading.
You want to work in the tech industry but still got that humanities itch to scratch.
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