What's the difference between artificial intelligence (AI),
machine learning (ML) and natural language processing (NLP)?

It can be a bit confusing. Let us break down all of the acronyms.

All of the acronymns 🆒

It’s almost harder to understand all the acronyms that surround artificial intelligence (AI) than the underlying technology. Couple that with the different disciplines of AI as well as application domains and it’s easy for the average person to tune out and move on.

Below we attempt to explain the important parts of artificial intelligence and how they fit together. At Sonix we are specifically focused on automatic speech recognition so we explain the key technologies with that in mind.

First let’s start with some of the most commonly used acronyms and their definitions:

  • Artificial Intelligence (AI) -the broad discipline of creating intelligent machines
  • Machine Learning (ML) -refers to systems that can learn from experience
  • Deep Learning (DL) -refers to systems that learn from experience on large data sets
  • Artificial Neural Networks (ANN) -refers to models of human neural networks that are designed to help computers learn
  • Natural Language Processing (NLP) -refers to systems that can understand language
  • Automated Speech Recognition (ASR) -refers to the use of computer hardware and software-based techniques to identify and process human voice

Artificial intelligence (AI) is the overarching discipline that covers anything related to making machines smart. Whether it’s a robot, a refrigerator, a car, or a software application, if you are making them smart, then it’s AI. Machine Learning (ML) is commonly used alongside AI but they are not the same thing. ML is a subset of AI. ML refers to systems that can learn by themselves. Systems that get smarter and smarter over time without human intervention. Deep Learning (DL) is ML but applied to large data sets. Most AI work now involves ML because intelligent behavior requires considerable knowledge, and learning is the easiest way to get that knowledge. The image below captures the relationship between AI, ML, and DL.

Sonix - Artificial Intelligence, Machine Learning, and Deep Learning and how they all stack up

There are many techniques and approaches to ML. One of those approaches is artificial neural networks (ANN), sometimes just called neural networks. A good example of this is Amazon’s recommendation engine. Amazon uses artificial neural networks to generate recommendations for its customers. Amazon suggests products by showing you “customers who viewed this item also viewed” and “customers who bought this item also bought”. Amazon assimilates data from all its users browsing experiences and uses that information to make effective product recommendations.

At Sonix we convert audio to text using machines. The principle underlying technologies are automated speech recognition (ASR) and natural language processing (NLP). ASR is the processing of speech to text whereas NLP is the processing of the text to understand meaning. Because humans speak with colloquialisms and abbreviations it takes extensive computer analysis of natural language to drive accurate outputs.

ASR and NLP fall under AI. ML and NLP have some overlap as ML is often used for NLP tasks. ASR also overlaps with ML. It has historically been a driving force behind many machine learning techniques.

Sonix - Where does Automated Speech Recognition & Natural Language Processing belong among Artificial Intelligence, Machine Learning, and Deep Learning

In summary, DL is subset of ML and both are subsets of AI. ASR & NLP are fall under AI and overlap with ML & DL. It's amazing how they are all intertwined.

The best automated transcription service in 2019 🚀

Easily convert your audio to text with Sonix

Sonix transcribes, timestamps, and organizes your audio and video files so they are easy to search, edit, and share. Start your free trial today—all features included, no credit card required.

Try Sonix for freeIncludes 30 minutes of free transcription

Other Sonix articles 📃

Tips on how to capture great audio

Hear from other Sonix users about how they record high quality audio

Why should you transcribe?

Five reasons you should be transcribing your audio and video files

History of speech recognition

How did we get to where we are today in speech recognition? Sonix explains

How to remove the metallic sound

The metallic, tin-like sound you hear in your audio is an unwelcome annoyance

Remove background audio noise

Background noise is annoying and lowers the accuracy of your transcript

Remove background noise in videos

Background noise is distracting in videos and don't transcribe well

Room tone: what is it?

Room tone is the naturally occurring noise in the environment during your recording

Audio transcription with Sonix

Sonix is the best online audio transcription service for 2019

Want accurate video transcription?

Sonix is the best online video transcription service. It's fast, accurate, and affordable.

Quickly convert audio to text

We accept over 100 different audio formats. Transcribe with Sonix today.

Transcribe your audio files

We accept many different audio formats (wav, mp3, m4a, ogg, and more)

Transcribe your video files

We accept many video formats (mp4, wma, mov, avi, m4v, and more)

Interview transcription with Sonix

Made for folks who conduct tons of itnerviews (incl journalists and researchers)

How to make voices sound better

Want to make voices sound more clear in your audio? It's easy.

Remove crosstalk and mic bleed

Make your transcription more accurate by post-processing the audio

How to mic a two-person interview

Make your transcription more accurate by recording it the right way

Six best tips for transcriptionists

Helping transcriptionists work faster and be more accurate

AI, ML, and NLP

Artificial Intelligence, Machine Learning, and Natural Language Processing

Is voice the next major UI?

We think that it will change how we interact with technology

Word error rate

How do you judge accuracy in the realm of speech recognition?

A comparison of automation services

Independently reviewed and Sonix scores the highest among automated services

2019 Webby Awards nominee

Top 10% of all sites entered, Top 5 in Machine Learning category