Automatic Speech Recognition Systems


Automatic Speech Recognition: A Definition and How it Works

“Hey, Siri – Read my texts.” If you’ve ever used Siri or Alexa, for example, to cue a command, then you’ve made use of automatic speech recognition systems. In fact, you’ve probably encountered speech recognition tools in more ways than you may even realize. From personal use cases to professional settings to increase efficiency, enhance productivity, and reduce errors, ASR systems are all ubiquitous for a reason. 

We’re going to define what automation speech recognition software is and how automatic speech recognition models work behind the scenes to turn words into actions. 

Speech Recognition

Siri enabled on an iPhone,

What are Automatic Speech Recognition (ASR) Systems? 

Automatic speech recognition systems are defined as the use of technology that combines machine learning and artificial intelligence to transform human speech into legible text. 

So, if you ever wondered, “Is automatic speech recognition AI?” you now that it certainly is. 

From podcast transcriptions, real-time captioning on social media platforms to speech-enabled software on manufacturing floors for mission-critical tasks, automatic speech recognition systems transform sound waves into written words. 

Key Components and Terms to Know 

While there is surely advanced technology working to power automatic speech recognition systems, we can break down how it works in layman terms:

Acoustic Model

The acoustic model (AM) predicts what word is being spoken based on sound, or phoneme. 

Language Model

The language model (LM) learns the sequences of words that are most likely to be spoken based on statistics of a language to then predict what words will follow next. It’s just like how Gmail or Apple will predict your next words in a sentence based on what’s already there at the start. 

Lexicon Model 

The lexicon model describes how words with their pronunciation are categorized by their phonemes, which are the units of word pronunciation. 


Decoding applies the lexicon, language, and acoustic models to then decipher what words are being spoken to create the transcript as an output. 

How Do Automatic Speech Recognition Models Work?

In a way, automatic speech recognition systems work in a similar fashion as people’s brains when they learn a new language. There’s an input and output, and between the two, the work of deciphering and understanding happens. 

In more technical terms, this is how the process flow functions: 

  • Audio Input and Signal Processing

The system intakes the soundwaves and processes them into a sequence of numbers that can be understood by the computer. 

  • Feature Extraction

The system works to ignore background noise and only identify the linguistic content that is relevant to the conversation at hand. 

  • Acoustic Modeling

Through application of acoustic modeling, the ASR system maps the string of acoustic features to its phonemes. 

  • Lexicon Modeling

Then, the lexicon model matches the phonemes to words. 

  • Language Modeling

And, lastly, the language model predicts the word sequence that is most likely correct. 

  • Decoding and Output

Decoding methods are used to most accurately reflect the words that have been spoken to create the text output. 

What is an Example of An Automatic Speech Recognition System?

Automatic speech recognition seems to be everywhere, especially since it’s in the palm of your hands on your mobile device with virtual assistants like Siri. 

But along with Siri and Alexa, did you know that automatic speech recognition software is what powers all of the following tools and features: 

  • Voice-to-Text Transcription
  • Virtual Assistants
  • Voice Commands in Consumer Electronics
  • Accessibility Features for Differently-abled Individuals
  • Automatic Subtitling in Videos

Person using voice recognition tool on phone while working

Person using voice recognition tool on phone while working,

Benefits of ASR

While the personal use cases of ASR have been widely known and quickly adopted, there are broader use cases in businesses in which automatic speech recognition is becoming the norm. 

This is because the benefits of automatic speech recognition systems are crucial and provide organizations with a competitive edge. For example, with the aid of speech-enabled tools, you stand to gain:

Increased Productivity

For starters, ASR helps you get more done in less time just by talking. You can talk through critical workflows that require utmost attention and care. Think about this– if you’re working in food manufacturing or logistics, chances are that you’re busy with machinery and need to keep your eyes up. Instead of having to run through inspection checklists with paper-based processes, you can use a tool like aiOla to speak through the checklist and work hands-free. Not only do you save time, but you also increase safety and accuracy. 

Enhanced User Experience

Overall, working with automatic speech recognition software can improve your experience with specific tools and workflows. You get to multitask, minimize errors, and run through critical processes more quickly, thereby increasing employee satisfaction by reducing the time it takes to complete tedious tasks. 

Accessibility for People with Disabilities

Importantly, ASR systems provide accessibility for people with disabilities who may otherwise have been limited. For example, hearing-impaired people can use ASR technology to convert words into text or those with physical disabilities can speak to type words. 

Automation in Transcription Services

You can also use ASR systems to automate transcription services, rather than having to physically type out every word being heard. This is a great time saver for doctors and those in the legal professions who have to transcribe notes and conversations. 

What are Common Challenges in Automatic Speech Recognition? 

As impressive as automatic speech recognition technology is, there is always innovation to be had. This is especially true because most systems may struggle or find challenges with accuracy due to: 

  • Accent and Dialect Variations
  • Background Noise and Environmental Factors
  • Speaker Variability
  • Vocabulary and Language Complexity

In some cases, particularly when using speech recognition technology in mission-critical businesses, a small inaccuracy or misunderstanding can spell disaster. 

That’s a major reason why aiOla is so revolutionary. aiOla is a speech-powered technology that’s been uniquely designed for business use cases as its patented technology combines automatic speech recognition (ASR) with natural language understanding (NLU). 

Along with its proprietary models for capturing and learning words, aiOla is able to fully understand business-specific jargon, which makes up over 50% of what is used for process completion in industries. Additionally, aiOla knows hundreds of languages, can discern any accent, and works in any acoustic environment while being able to filter out background noise that’s irrelevant to the task at hand. Sounds too good to be true? See aiOla in action here.

Final Words 

By answering, “What are the different types of ASR systems?” you can select the right tool based on what you’re trying to accomplish. 

To exemplify, if you wish to have a personal virtual assistant, then Alexa or Siri are around to help. For businesses that seek enhanced productivity and the ability to complete mission-critical tasks hands-free with a total understanding of business-specific vocabulary, then a solution like aiOla is right for you! Plus, aiOla helps capture and structure otherwise lost data, which aids in process improvement and pattern recognition to resolve issues even before they occur. 

As you can see, across the board, automatic speech recognition systems are transforming how people work and live. Don’t get left in the dust without being able to speak to complete!