How Does Voice Recognition Work?

We use technology more and more in our daily lives, especially in professional settings when we need to take detailed notes. Instead of jotting down every last word, we can now use voice-recognition software to notate what was said in a meeting or courtroom.

This post will cover some key topics about voice recognition:

  • Speech-to-text conversion: First, a speaker’s sound waves are fed into a computer and broken down. The continuous voice signals are chopped up into samples as small as thousandths of a second. This process is known as sampling and is essential before the next few components take place.
  • Preprocessing: Those speech fragments that were broken down above are then preprocessed by the computer. The computer takes the audio sound waves and converts them into numbers (bits) that can be identified by either of the computer systems below.
  • Recurrent neural network: Scientists have developed algorithms capable of processing huge data sets similar to how a human brain works. These are called recurrent neural networks (RNNs) and, just like our brains, they are constantly learning. RNNs are responsible for predicting the next letters in a word, increasing the system’s efficiency.
  • Long short-term memory: A traditional RNN isn’t capable of processing very long sequences, which is where long short-term memory (LSTM) comes into play. An LSTM remembers values over time and separates them into different classes to better predict the next words in a sentence.

Why is voice recognition so difficult?

With how far we’ve come over the past few decades, it may seem like AI-dictation software makes dictation and transcription a breeze—but that couldn’t be further from the truth. These are a few items that make voice recognition so difficult:

  • Noise suppression: Human ears and brains are able to get rid of background noise and focus on a single speaker. Computers can’t do that. They take all of that noise as part of the input, throwing off the AI software.
  • Speed: We’re able to understand slow and fast speech as well as high-pitched and low-pitched voices filled with emotion. Even the latest and greatest AI software struggles with this. Most systems struggle to understand speech faster than 200 words per minute.
  • Accents: Someone with a southern drawl or some other accent can be hard to understand if you’re not from the area. If we have trouble understanding that speech, image what computers think. It’s always helpful to have a human transcriber when someone with an accent is speaking, as AI software can’t keep up.
  • Context: We can understand the context of a conversation with even the simplest of audio or visual prompts. Since AI software doesn’t get those prompts, it can’t always properly transcribe a conversation or speech.

We have the AI dictation software for you

Whether you need to record trial proceedings or take note of what happened in a conference, turn to Efficiency, Inc. Our voice recognition software is second to none when it comes to recording every last detail. Reach out today to see what we can do for you.

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