November 2018
Intermediate to advanced
322 pages
7h 54m
English
Content preview from TensorFlow Machine Learning Projects
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5: Speech to Text and Topic Extraction Using NLP
Recognizing and understanding spoken language is a challenging problem due to the complexity and variety of speech data. There have been several different technologies deployed to recognize spoken words in the past. Most of those approaches were very limited in their scope, as they were unable to recognize a wide variety of words, accents, and tones, and aspects of spoken language, such as a pause between spoken words. Some of the prevalent modeling technique for speech recognition include Hidden Markov Models (HMM), Dynamic Time Warping (DTW), Long Short-Term Memory Networks (LSTM), and Connectionist Temporal Classification (CTC).
In this chapter, we shall learn about various options for speech ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.