Voice Recognition System

What is voice recognition?

Voice or speaker recognition is the ability of a machine or program to receive and interpret dictation or to understand and carry out spoken commands. Voice recognition has gained prominence and use with the rise of AI and intelligent assistants, such as Amazon's Alexa, Apple's Siri and Microsoft's Cortana.

Voice recognition systems enable consumers to interact with technology simply by speaking to it, enabling hands-free requests, reminders and other simple tasks.

Today, we have two types of voice recognition:

• Text-Dependent –  depends on the specific set of words the person says – you need step-up authentication and identity verification and in order to be activated, the user has to say the necessary phrase. 
• Text Independent – does not depend on a specific text yet relies on conversation speech. The authentication does not require for the user to say a set of required phrases. 

How does voice recognition work?

Voice recognition uses technology to evaluate the biometrics of your voice. That includes the frequency and flow of your voice, as well as your accent. Every word you speak is broken up into segments of several tones. This is then digitised and translated to create your own unique voice template.  

Artificial intelligence, deep learning, and machine learning are the forces behind speech recognition. Artificial intelligence is used to understand the colloquialisms, abbreviations, and acronyms we use. Machine learning then pieces together the patterns and develops from this data using neural networks. 

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What are the advantages and disadvantages of voice recognition?

The advantages of voice recognition are:

1. Creates personalized content

The best way to add more personalization to your services is to enable your customers to easily and quickly present their needs – this can be accomplished by voice recognition technology.  

For example, today’s market consists of customers who are digitally literate or e.g. Millenials who are considered the digital generation – voice recognition technology would bring a personal touch for their needs and may be a winner for them.  

Those personal conversations can be developed with Voice AI which may provide better connection between the company and the individuals.

2. Saves time

Voice recognition technology is being built-in to more devices and gadgets in order to make life easier as voice inputs are far more efficient than typing. 

Voice recognition technology is improving each day and as per The University of Stanford, it has improved to the extent where it is able to be much faster and more accurate with text outputs (e.g. dictation on a mobile device etc.) than a person could be when typing on a keyboard. 

If such technology is implemented, businesses can streamline administration processes and mitigate the burden of typing and other similar tasks while enabling employees to focus on more complex aspects of the job. 

3. Increases productivity

When talking about workplaces, voice recognition can provide support and assistance with task-management duties such as setting up conference calls, scheduling meetings or setting up reminders, like with Amazon’s Alexa, for example. Such an approach enables companies to streamline the process for everyone leading to improved productivity and efficiency. 

With the development of voice recognition, it is now possible to acquire relevant information upon a voice instruction or request data for any specific project – all these activities can now take less time than it would usually do if we did it manually.

 Translational capabilities enable people who speak different languages to communicate – the technology has the capability to translate the content into the target language which helps to remove the language barriers within daily business operations. 

4. Accessible

As voice technology requires only voice, it is a great option for people with motorical disabilities or difficulties to communicate much easier to your business. 

Such technology brings power to people who originally could have accessed it either at slow pace or not at all.

In addition, using voice recognition software can significantly help people with other kinds of disabilities like arthritis or hand tremors which can worsen if typing too much during the day. 

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The disadvantages of voice recognition are:

1. Errors misinterpretations of speech

Not all words are correctly interpreted with voice recognition technology. This is especially the case when there are multiple people speaking in different accents. This might cause the voice recognition technology to confuse the words that are spoken with other words that might sound like them in the accent that the software is used to or trained on.

This might disrupt tasks that were assigned to the software, especially when the software has to deal with slang words, acronyms, jargon, etc.

Sometimes this might make it necessary for a human to go through the recorded audio as well as the transcribed text to minimize the amount of errors in the transcription.

2. Privacy of voice data

With more devices making use of voice recognition technology, there are greater risks to data privacy. The manufacturers might be able to track recorded voice data, and there have been concerns in the past about manufacturers listening to private conversations. Organizations need to offer more effective privacy controls to the users of their devices and software.

What are the types of speech recognition?

Speech recognition is widely used for multiple applications like calling cards and phone banking services allowing people to answer questions vocally instead of pressing numbers on the phone screen to send Dual Tone Multi-Frequency (DTMF) signals.

There are two types of speech recognition:

1. Independent speech recognition

Independent speech recognition is about recognizing vocabulary items irrespective of who is speaking. For populations of a smaller size, independent speech recognition can work at an accuracy of 95% or even higher.

2. Dependent speech recognition

Dependent speech recognition involves recognizing vocabulary items that are spoken by a specific speaker. This type of speech recognition needs users to train the system to recognize vocabulary items in a specific voice or accent. These speech recognition systems build templates that they use for future comparisons to real-time text. Dependent speech recognition systems can perform at an accuracy of 98% or more, except in situations where the user who created the templates has a substantial change in their voice characteristics.