Voice recognition vs speech recognition: the difference and why they matter
The difference between voice recognition and speech recognition may seem arbitrary, but they are actually two key functions of virtual assistants. Essentially, voice recognition is recognising the voice of the speaker whilst speech recognition is recognising the words said. This is important as they both fulfil different roles in technology. Voice recognition allows for security features like voice biometrics, whilst speech recognition allows for automatic transcriptions and accurate commands.
If you didn’t know the difference between the two then you are honestly not alone. Most people use them interchangeably to mean the same basic thing. But AI voice commands are everywhere nowadays, with Apple’s Siri, Microsoft Cortana and Amazon’s Alexa, commanding our electronics with our voice is the sci-fi dream come true. So, here is a quick rundown of everything you need to know about the future of electronic command.
What is voice recognition?
Voice recognition is the process that allows Artificial Intelligence to recognise and decode human speech patterns. It essentially allows for your computer, smartphone or virtual assistant to understand what you’re saying and respond. It is everywhere — in fact, 9.5 million people in the UK will use a smart speaker, which has increased 98.6% from 2017, and it is only predicted to become more prevalent in the future.
What is speech recognition?
Speech recognition uses a process known as Natural Language Processing (or NLP) to allow a computer to simulate real human interaction. Nominally, what it does is take normal human speech and, using machine learning, respond in a way that mimics human responses. It is essentially how computers in science fiction interact, though with generally fewer disasters.
The difference between voice recognition and ASR
The difference between Voice Recognition and Automatic Speech Recognition (the professional term for AI speech recognition, or ASR), is the way in which they process audio, and how they respond to it. Voice recognition is something you will use with devices like Amazon Alexa or Google Dot. It listens to your voice in real-time and responds. Voice Recognition has limited functionality, usually restricted to the task at hand, but is the process through which most digital assistants operate.
ASR is different in that rather than recognising voices, it instead recognises speech. Using NLP, it can accurately generate a transcript of audio, creating real-time captioning. ASR is not 100% perfect — in fact, in perfect conditions it rarely exceeds 90%-95% accuracy. But it makes up for it by being fast and cheap.
Essentially, ASR is what someone said, whereas Voice Recognition is who said it. Both processes are very closely linked and often you may find them being used interchangeably. The differences are subtle but striking.
Why do they matter?
So, why do these two technologies matter? Well, they matter because right now, you’re most likely reading this on a device with AI speech recognition technology as well as AI voice recognition technology. This technology is all around us and is only going to become more standard as the decade continues. It is reported that by 2025, this industry could be worth $26.79 billion dollars, or £20.82 billion pounds.
Getting to grips with this technology now, and figuring out the best ways to utilise it, will be of great help to your businesses growth over the next five years
When do you need voice recognition?
There are plenty of benefits to employing voice recognition into your workflow:
- User Verification — HSBC launched voice biometrics as a security measure on their accounts in 2016. Since then, they have reported a saving of £300 million in fraud. Using voice as a password increases security whilst saving money on biometrics.
- More efficient and faster operations — The ability to precisely communicate with technology using just your voice eliminates the need for error scans and instead allows for more accurate workloads at a faster pace.
- Convenience — Having your speaker or your computer recognise your voice from the outset means that after the initial set-up, the computer adapts to your voice and speaking pattern, reducing the need for tinkering and allowing for better communication and task management.
When do you need speech recognition?
Speech recognition is used across industries as fast operating transcription services, as well as in software computer help.
- Note-taking — Devices such as Alexa, Google Home and Siri employ speech recognition to transcribe your thoughts into notes. This allows for specific responses through NLP, and can make your virtual assistant simulate personality.
- Disability help — Speech recognition is vital for people with disabilities. Auto-generated subtitles, Dictaphones and Text relays allow for deaf, hard of hearing and people with learning difficulties to engage with media and the wider world. It is a necessary innovation for a lot of people and something that drives technology further.
- Video and archiving — It is being employed increasingly in the video creation field. Along with object detection, many Software as a Service Providers are employing it in the creation of metadata and archiving.
When should you opt for transcription services that use professional transcribers?
ASR vs Human transcription is a topic that is ongoing and, on the surface, seems complicated. But the differences between the services are actually fairly pronounced. It boils down to three main factors: cost, speed and accuracy.
When we talk about cost, we really talk about money and time. When it comes to which is cheaper in monetary terms, it’s ASR. For transcriptions, ASR is generally cheaper, coming anywhere from free to use apps to £0.07/per minute services, compared to human transcription which can come in anywhere from £0.50/per minute to £2.00/per minute.
This is good as most smart devices have some form of transcription software built-in, but for more professional works, such as legal transcription, accuracy becomes a factor. This is where the time cost comes in. ASR is not as accurate as human transcription, meaning that whenever you use ASR you will then need to spend time going through the transcript and fixing errors.
ASR is faster than human transcription. A computer can obviously process things faster and create a transcript sooner than a human. But you then also need to factor in the time cost again. If the audio is heavy with background noise or there is more than one speaker, then you may find the transcript takes longer to produce.
Accuracy is really where the difference lies. For personal note-taking, when there is only one speaker, then ASR may sufficeBut when accurate, verbatim transcripts are required, human transcription services are superior.They offers far more flexibility in content, ranging from detailed notes to full intelligent verbatim, with fewer mistakes.
Use AI recognition for the right tasks
Artificial Intelligence is an exciting and evolving field of study and innovation. It is constantly improving and advancing — we can see that in the new generation of smart home devices that offer more connectivity and more intelligent design. There is a space for advanced AI recognition in most industries where speed and convenience are important.
It is not a catch-all solution, however. As with every task in business, there is no one correct answer. Your use of AI depends entirely on your unique set of circumstances and it’s important to bear this in mind when looking at how you can implement AI solutions. Sometimes the human touch is better for a task. But thinking about it, and how it can offer solutions to your problems now, will put you in a much better position for the future.