Google Cloud: AI Speech-to-Text with Python 3

Description

In this course, you will learn :

• How to integrate Google's powerful Speech-to-Text AI models into a Python programme.
• Begin by learning about the main use cases for Speech-to-Text (STT) and an overview of the API.
• You will then run some API demo code to create a transcription for an audio file. Don't worry, you'll go over each line of code to ensure you understand it.
• Learn about recognition configuration, speech adaptation, and the various speech recognition models.
• Learn about the word error rate and how to calculate transcription accuracy.
• Able to incorporate STT into your own Python projects and have a valuable new skill to add to your resume.

Syllabus :

1. Your First Program

• Simple Transcription Demo Code
• Demo Code Deep Dive
• Quiz

 

2. Recognition Configuration

• Create a Storage Bucket and Transcribe an Audio File
• Punctuation
• Multichannel Audio (Stereo)
• Enhancing a Multi-channel Transcript
• Speaker Diarization

 

3. Speech Adaptation

• Overview of Speech Adaptation
• Phrases
• Classes
• Boost
• Boost tuning

 

4. Models

• Choosing the Recognition Model
• Enhanced Phone Call Model
• Summary Quiz

 

5. Word Error Rate WER

• How to Measure Transcription Accuracy
• Identifying the Right Boost Value
• WER Demo

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