When you were little, one of the things that you saw in sci-fi films was how the characters were using voice commands to operate different devices. Back then, it seemed like something that you’d see 50 years later. But thanks to the innovation of modern technology, you can see it being used right now.
Speech recognition is also being applied in many spheres of life these days. From virtual assistants to YouTubers using it to convert speech to text, the possibilities are limitless. But how does it work?
The way things work behind the scenes in speech recognition technology is really interesting. This article focuses on those core concepts to help you understand the process. At the same time, it takes a look at the different ways technology is being applied in the modern world.
A Quick Overview Of Speech Recognition Technology
So, what is speech recognition? From what you’ve already seen, it’s a technology that converts the speech spoken by someone into actual text. It’s similar to how cases are transcribed in courts. Only here, it’s all done digitally without the need of a human being.
If you take a look at the development history of speech recognition, you’ll have to go as far back as the 1950s. That’s when the concept was first born. But it wouldn’t be until the 90s when the first speech-to-text software like VoiceType and Dragon NaturallySpeaking.
The modern incarnations of the speech recognition technology that exists today came to being after advancements in deep learning. The first product that utilized this was Apple’s virtual assistant, Siri back in 2011.
How Does It Work?
Now that you’ve had the chance to take a quick look at the historical background, you should get down to the real stuff. How does this work? How is a speech from a human being or an audio transformed into text? Check it out.
Input and Analysis
The process begins by taking input first. This can be a line spoken by someone into a microphone or an audio file. Once the program receives the input, it will then analyze the sound waves present in the input.
The analysis helps it filter out different acoustic features. By differentiating the pitch and intensity of the sound, the software prepares the input for the next step, which is interpretation.
The speech recognition software takes the analyzed input and breaks it down into fundamental phonetic units called phonemes. This process is important as these small units are capable of changing the meaning and intent behind a word.
Modeling and Decoding
The phonemes are then fed to a language model that predicts phrase combinations. By guessing which string of words can be placed together and comparing it with the input, the model generates a probable output.
But that’s not the end. The software then takes the phonemes and model output to decode the input. The text that you see in the software is the culmination of all of these different inputs.
Different Applications Of Speech Recognition Technology
By now, you should have a basic understanding of how this technology works. Now, you can finally learn more about the different applications of speech recognition technology.
A very popular use of this technology is for transcribing online videos. Platforms like YouTube, Facebook and Instagram and among others use this. Online course websites with video lectures also make use of these speech-to-text options to help the students learn a new skill.
This also makes the video content more accessible to viewers. A viewer can be hard of hearing or they might not speak the native language used in a video. Fortunately, having transcriptions in is a big help and makes sure that no one is left out.
On Google Search, there is a small icon on the search bar, clicking that will allow one to activate voice search. By speaking out loud you can now search for what you’re looking for. This hands-free feature makes things easy and enhances the user experience.
Aside from Google, this feature can also be found on YouTube. A lot of eCommerce sites are also offering this feature to their users for an improved user experience.
Having virtual assistants is a blessing in disguise in this fast-paced world. Google might have been late to the party, but the experience that it’s able to deliver is on par with Apple’s Siri.
These virtual assistants make everyone’s lives much easier. When you need to do mundane things like a grocery list, you just pass that on to your virtual assistant and all is taken care of. Have a busy day ahead of you? Just let your virtual assistant know what needs to be done and it’ll automatically complete the task.
Challenges And Possible Solution
While the technology does work wonders, there are still some ongoing challenges that researchers are still trying to address. For instance, the variations in dialect and accents. Speech recognition systems aren’t yet developed to the point where it’s able to decipher accents with 100% accuracy.
Another challenge is dealing with background noise. It’s impossible to program software to anticipate every possible kind of background noise. This is one of the issues that will either require a lot of time or a revolutionary approach that’s able to eliminate any kind of background noise.
One of the possible solutions to every kind of challenge out there is coming up with better speech recognition models. To accomplish that, better data collection and preprocessing techniques are needed.
Data scientists should also consider new approaches to improve the performance of the models. By making adjustments to the process, it will be possible to reduce the rate of wrong interpretations.
From what you’ve seen, you can tell that there’s no denying the benefits that can be enjoyed from the modern applications of speech recognition technology. Scientists and researchers will need to come together to make improvements and come up with new ways of using speech recognition.
Hopefully, the changes will allow the world to finally experience a completely hands-free digital experience.