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Spoken Language Processing in Python

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5

(3)

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Before we can read, it is important to learn how speak before we can read. In today's digital age, speech is still the primary mode of communication. Spoken Language Processing allows you to load, convert, and transcribe audio files in Python. This article will show you how Python handles raw sound. Next, we'll show you how Python handles raw audio.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Intermediate Python

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Introduction to Natural Language Processing in Python

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Supervised Learning with scikit-learn

What You Will Learn

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Learn to load, transform, and transcribe human speech from raw audio files in Python

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You'll start by seeing what raw audio looks like in Python. And then finish by working through an example business use case, transcribing and classifying phone call data

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You'll learn the first steps to working with speech files by converting two different audio files into soundwaves and comparing them visually

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In this section, you'll learn how to use the SpeechRecognition library to easily start converting the spoken language in your audio files to text

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Then you'll perform sentiment analysis using NLTK, named entity recognition using spaCy and text classification using scikit-learn on the transcribed text

Course Instructors

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Daniel Bourke

Machine Learning Engineer and YouTube creator

Machine Learning Engineer who creates YouTube videos and writes about the intersection of health, technology and art.

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