It’s an exciting time to be a developer in the voice computing space: 1 in 4 searches on Google are now voice-enabled, Amazon Alexa just passed 10,000 skills, and 100 million calls are completed on WhatsApp daily. But where do you go to start learning how to code in this field?
Whether you are a veteran developer or just starting out, this book guides you through the process of building voice-based applications in Python.
Applies >20 Python libraries to help you solve voice-related problems faster.
Over 200 scripts are provided on GitHub to get you up-and-running quickly.
Become involved in the larger open source voice community, 45,000+ people and counting.
Voice computing is the discipline that aims to develop hardware or software to process voice inputs. You can learn more about this field in the introductory video here.
The #Voicebook focuses on building voice computing software applications in Python.
This book is geared for beginners or veteran programmers alike. Many of the chapters start off simple then go into more advanced topics, so you're likely able to get something out of it regardless of your background.
Specifically, by the end of the book you'll be able to:
• Understand how to read/write, record, clean, encrypt, playback, transcode, transcribe, compress, publish, featurize, model, and visualize voice files
• Build your own voice computer and voice assistant from scratch
• Design cutting-edge microservice server architectures on top of Docker and Kubernetes
• Get access to 200+ starter scripts in a GitHub repository
• Become involved in the larger open source voice community
Simply, there are relatively few resources to learn how to write voice-enabled software that are straightforward and easy-to-understand.
Throughout the past 6 months, I have had repeated requests for resources to learn voice computing. There are a few great places to start - like sharing the documentation of a few modules (e.g. LibROSA); however, this is often not enough to get through the activation necessary to build good software. I would find myself taking some breakout sessions with Fellows to hack code together to model voice files. Soon, my time became limited as a CEO and I could not help many eager developers wanting to enter into this field.
This book is therefore a first attempt to scale this knowledge in a more repeatable way.
NeuroLex Laboratories is a company with the goal to make voice computing accessible to everyone. Over the past year, we have expanded our team to over 15 people, launched 7 research pilots, built a pipeline of over 80 startup and research collaborators, and have been featured in various press outlets like the Atlantic and PsychNews.
The Innovation Fellows Program is a competition to engage outstanding individuals with NeuroLex. Specifically, you propose a demo project alongside a mentor in one of three categories: research, data science, or software. You then execute this demo project over a 3 month period either individually or as part of a group. The program culminates in a Demo Day where you present your project to a panel of judges. Through this structure, you can gain hands-on expeirence and be part of a sustainable, lifelong community.
If you're interested, you can apply for the program @ innovate.neurolex.co
Please use this information:
Schwoebel, J. (2018). An Introduction to Voice Computing in Python. Boston; Seattle, Atlanta: NeuroLex Laboratories. https://github.com/jim-schwoebel/voicebook