Natural Language Processing: Crash Course Computer Science #36

Today we’re going to talk about how computers understand speech and speak themselves. As computers play an increasing role in our daily lives there has been an growing demand for voice user interfaces, but speech is also terribly complicated. Vocabularies are diverse, sentence structures can often dictate the meaning of certain words, and computers also have to deal with accents, mispronunciations, and many common linguistic faux pas. The field of Natural Language Processing, or NLP, attempts to solve these problems, with a number of techniques we’ll discuss today. And even though our virtual assistants like Siri, Alexa, Google Home, Bixby, and Cortana have come a long way from the first speech processing and synthesis models, there is still much room for improvement.

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[alexanderkoller]

Hi, I'm a professor of computational linguistics in Germany. I just wanted to say that your video is one of the best explanations of natural language processing for non-experts that I've ever seen. I'm really impressed - great job!

[Chrnalis]

This is how computer science should be taught. The motivation and big picture is important.

[etiennepesce]

"It wasn't evil, it was efficient" might be the most terrifiying sentence I've ever heard in my life.

[allanjoarder]

This series is so fantastic. I get super excited to hear real-world examples and helps me envision the possibilities in the future.

[ReplacedTea]

I can't believe I've watched all 36 of these. Keep up the good computer science.

[kaptenteo]

Will the foreshadowing of Crash Course Linguistics ever cease?!

[JesseMcCall]

Oh my gosh, this is the best channel I've subscribed to in a long time (on par with SmarterEveryDay)! Kudos!

[ivannaivanova]

I love how you gave an example with Siri! Thank you for all your work! You are amazing.

[old-moose]

Elisa was the starting point of doctoral interest in natural language for education. We've come a long way from Xerox Sigma 7s and PDP-11s working through teletypes and VDTs. I think we are about ready to start doing the natural language teaching that I dreamed about all those decades ago.

[angeldude]

One minor issue is that with speech interfaces becoming more common and more complex, some people will over estimate how human they are and get annoyed when it doesn't understand what the user thinks is a perfectly simple request.

[mattkuhn]

Aw yiss, this is my jam! Thanks for this video - I’m in grad school working on an MS in Computational Linguistics, so NLP is what I do every day. I actually just finished writing a simple part of speech tagger the other day!

[safflower_s]

thank you for the episode! i knew a lot of it, but this video managed to structure everything so neatly that i feel like i understand the topic so much better now :>

[scfoxcode]

Absolutely fantastic video. A great overview of the topic making it easy for me to learn more about the parts that interest me. I will be watching more of these this weekend

[kds]

I recall on my TRS-80 Model 1, Level 2 with EI and disk - I had a speech synthesizer hooked up and a speech recognition module. That was great fun - learned about phonemes through that.

[typograf]

I'm 55. It has been "pretty soon" that voice recognition would work properly for most of my life. It is now in common use - and it still does not work. Perhaps if I live to a 110, but I will take no bets on that.

[CuriousSomeone]

Brilliant! So clearly explained. Well done!

[cristian]

This videos are just so awesome!!!, great job.

[unimportantaccount]

Try turning on automatic captions. For clearly spoken stuff like what is on this channel, they are super accurate now.

[natbud]

It would be great to have a similar series on implications of technical progress with philosophers and social studies experts commenting on the relationship between the tech and our society.

[qlifee]

Thank you, I always wanted to know more about this topic 👍