Digital voice assistants like Siri, Alexa, and Cortana – are all here to very much be a part of our lives. Like for instance, “Alexa, wake me up at 6 am”, “Alexa, please find my car keys”. Just like a genie from the folklore, these voice assistants process all our voice commands at the drop of the hat.

When everything at the touch of a keypad had become the new normal, the Voice technology just created a new milestone. Popular digital voice assistants such as Amazon’s Alexa, Google Assistant, Microsoft’s Cortana and Apple’s Siri are brought to reality something that we could only dream of.

digital voice assistants

Arthur C Clarke, an eminent science fiction author who wrote 2001: A Space Odyssey in the late 1960’s created the character HAL 9000, which was an artificially intelligent computer with an ability to do speech recognition and Natural Language Processing (NLP). 50 years back, Clarke could predict that in the future, humans could converse with machines that are artificially intelligent. Today, this has become reality.

Have you ever thought about the science that works behind these voice assistants? Accessible through smartphones, tablets and other internet-backed devices, Digital Voice Assistants spring into action at the mention of a verbal command.

How does this happen? This is made possible by cutting edge technology at various stages- Speech Recognition, Natural Language Processing, Machine Learning and Cloud-based technology.

The moment you say “Pick up my books”, your digital voice assistant recognises your voice commands. Speech recognition means conversion of speech into text. Every user will have a different pronunciation, diction, tone and dialect.

The Speech recognition technology of these Voice assistants is extremely advanced and can process all these variations because of linguistic and semantic analysis.

 

Once the speech is converted to text, it is now time to understand the text. This is where NLP or Natural Language Processing comes to the rescue. NLP helps to convert unstructured text into structured text that the gadget can understand. NLP matches the utterances (the human commands) to the right Intent.

There are different NLP models which have different levels processing capabilities of the variations in utterances. These Voice Assistants can identify keywords and the position of the keywords in the verbal request.

The intent of the command and the corresponding slot values are collected into a well-ordered data structure which is passed along to a cloud-based service capable of processing various intents. The information retrieved is in the text form and needs to be converted into cloud services that empower voice interfaces that have a collection of pre-recorded words to spell out the results.

To make it sound more conversational, these services also use a mark-up language especially for speech synthesis. This mark-up language supports the use of emphasis, tonality, pitch, sound and the usage of words that are specific to a particular area.

Latest trends

The work of Digital Assistants is becoming more automated as the time progresses. They will be more capable of understanding the request even before it is placed. This is possible through Machine learning. Through this technique, machines that can learn to work on their own from their previous experiences. Machine Learning allows the digital voice assistants to understand patterns in your use and re-create the action without even placing the command.

Amazon is now opening up Alexa to other companies to programme it accordingly. This means that companies can now make Alexa compatible according to its products. For example, Ford can make Alexa programmed according to its cars. Maybe in the future, Alexa can start the car on just a command and put on the air-conditioner even before you enter the car. The possibilities are unlimited.

Voice Assistant will continue to up their accuracy levels

The conversion of speech to text and the Natural Language Processing (NLP) models are using Machine Learning algorithms to bring about constant improvement. The level of accuracy in deciphering the meaning behind each utterance or command will only get better as Machine Learning continues to evolve.

We can very well expect that in the coming years, these machines will help the digital voice assistants to achieve human like accuracy and understanding.