What Is Speech Recognition Software?
It’s highly likely that you’ll have encountered some form of speech recognition software, even if you don’t realise it. This useful software has applications in many different areas: it has been used for years to transcribe consultations into medical records and to handle incoming calls in customer support (more recently, it’s been used to create virtual assistants like Amazon Alexa).
Although your voice has probably been transcribed by speech recognition software at some stage, you may not really know what it is. Over the course of this guide, we’ll define speech recognition software, explain how it works, discuss some of its benefits, and highlight how it is used in call tracking.
Defining Speech Recognition Software
Speech recognition software is a form of natural language processing capability that enables a computer to identify human speech, process it, and convert it into a format that can be read by humans and machines. As such, this type of software is often referred to as voice-to-text software.
How Does Speech Recognition Software Work?
First experimented with in the 1970s, speech recognition software has come a long way since its inception. The technology works by recording spoken words, identifying them, and then turning them into text using algorithms.
The algorithms behind this process are trained by human input and learn to recognise human language. Engineers also teach speech recognition software to distinguish between the sound of someone speaking and natural, ambient noises that might otherwise interfere with its understanding.
As speech recognition algorithms are trained to understand language through real-world input, they become accustomed to the type of voice on which they were trained. If a user has a significantly different accent or intonation to the training voice, then the software may fail to comprehend them.
Speech recognition software can be used in a number of different ways. Each application uses the text that is produced by the process for a different purpose. In the case of Amazon Alexa, the text is used as a command for the smart speaker; traditional voice-to-text dictation applications simply provide you with the text in a word processor.
Over the past decade, the use of speech recognition software has become much more widespread and its accuracy has increased tremendously. Google’s version of the software has benefitted from the addition of neural networks – sets of algorithms modelled on the human brain – and has reduced its error rate by 30% since 2012.
Why Use Speech Recognition Software?
There are many benefits to using speech recognition software. When used for dictation purposes, this software is advantageous because it generally converts spoken words into text much faster rate than if the words were typed out manually. Extensive transcription tasks such as those required in the medical field are carried out much more efficiently with the use of speech recognition software.
In customer service, speech recognition software has enabled companies to address customers’ concerns without using a human agent. More enquiries can be dealt with as a result, improving the efficiency of the service and providing cost savings. In addition, the software can collect customer data the could not otherwise be recorded using automated means, including names and addresses.
Using Speech Recognition for Call Tracking
In the context of call tracking, speech recognition software is used to transcribe the content of phone calls that have been recorded in the system. The sophisticated software included in Calltracks packages can even distinguish between the agent and the caller, delineating between them in the transcript that is produced.
Organisations can then use these transcripts in a number of ways. They are commonly analysed for data that can be used in the process of training customer support and sales staff, helping companies to recognise what they are doing right and what could be improved. Some firms also use the call tracking transcripts to inform keyword research for their search marketing efforts, discerning important keywords from the speech of callers and agents.