Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Learn OpenAI Whisper
  • Table Of Contents Toc
  • Feedback & Rating feedback
Learn OpenAI Whisper

Learn OpenAI Whisper

By : Josué R. Batista
4.9 (13)
close
close
Learn OpenAI Whisper

Learn OpenAI Whisper

4.9 (13)
By: Josué R. Batista

Overview of this book

As the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.
Table of Contents (16 chapters)
close
close
Free Chapter
1
Part 1: Introducing OpenAI’s Whisper
In Progress | 0 / 1 sections completed | 0%
4
Part 2: Underlying Architecture
In Progress | 0 / 1 sections completed | 0%
7
Part 3: Real-world Applications and Use Cases
In Progress | 0 / 1 sections completed | 0%
11
Chapter 8: Diarizing Speech with WhisperX and NVIDIA’s NeMo
In Progress | 0 / 5 sections completed | 0%
14
Index
In Progress | 0 / 2 sections completed | 0%

Milestone 7 – Executing the training loops

To begin training, just run the following command:

trainer.train()

Figure 4.1 shows an example of the output you can expect to see from the trainer.train() command’s execution:

Figure 4.1 – Sample output from trainer.train() in Google Colab

Figure 4.1 – Sample output from trainer.train() in Google Colab

Each training batch will have an evaluation step that calculates and displays training/validation losses and WER metrics. Depending on your GPU, training could take 5–10 hours. If you run into memory issues, try reducing the batch size and adjusting gradient_accumulation_steps in the declaration of Seq2SeqTrainingArguments.

Because of the parameters we established when declaring Seq2SeqTrainingArguments, our model metrics and performance will be pushed to the Hugging Face Hub with each training iteration. The key parameters driving that push to the Hub are shown here:

from transformers import Seq2SeqTrainingArguments
training_args = Seq2SeqTrainingArguments...

Unlock full access

Continue reading for free

A Packt free trial gives you instant online access to our library of over 7000 practical eBooks and videos, constantly updated with the latest in tech

Create a Note

Modal Close icon
You need to login to use this feature.
notes
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Delete Note

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Edit Note

Modal Close icon
Write a note (max 255 characters)
Cancel
Update Note

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY