We are all familiar with how the marketing of Alexa and its models are on the fly. Alexa is the new voice search interface that does something or rather obeys a command by recognizing the voice.We have also seen on TV how Google is allowing voice search on a phone when the lady in a function searches for something by simply ‘talking.’ Fascinating isn’t it?
This fascination has created waves in the tech world, and predictions around it say that ‘Voice’ will make up to 50% of all searches.Voice Recognition and tech associated with it are leveraged to power many applications.
It’s in automobiles, cell phones, home automation, and what not? Have you ever thought if Websites could be capable of doing the same.The answer is yes, but the solution isn’t all that simple. For starters, it’s important to know what a ‘Schema Markup’ in Voice Tech can do.This blog explains all this and more.
Voice Schema Markup
If you are into tech, you would very well understand what HTML means. For those of you who don’t, it’s a coding language that recognizes different elements like paragraphs, headings, titles, sections, and so on within a text space. These are marked within specific, pre-defined tags.
Similarly, for voice data, there is a structured data markup (tags) that you can add in your website’s HTML. This will enable Search Engines to completely understand what the website is about, which will, in turn, enhance SERP display. In other words, this is voice search on structured data.
Just like HTML, the schema is designed to be Universal search engine language. This will provide a collection of shared vocabularies that major search engines can understand.The vocabularies are collected by open community process powered jointly by Google, Yahoo, MS, Yandex using public-schemaorg, and Github schemaorg.
A full list of items that can be used as the markup is in schema.org. Schema can markup items such as people, recipes, products, and so on. Every item is identified using primary and attributed properties.
These properties are like keywords that the search engines pick up. This will help voice search optimization.
Adding Schema Markup
- Enter the raw HTML file or enter a URL
- Select the option Start Tagging
- Select important sections of the page
- Create a new HTML page with this by generating a new page code. Replace the old with the new.
This is Google’s new schema markup which is still in its beta stage. Under this markup, sections can be highlighted for Google applications such as Google’s assistant and Alexa to speak out aloud as answers or responses.
This is called TTS – Text To Speech playback. This is key to unravel audio browsing. Can you imagine the potential reach of this?
Its currently launched it in the US alone. Once there is enough strength on registered users in other countries owing web inventories, then Google may prep to launch this tech in their areas.
Obviously, it has to suit and be designed to power environments that use audio strength. Pictures, videos, images, diagrams would not be extensively used in audio searches.
The use of easy to read and simple words are ideal in such sections. Keeping it short and conversational and also interpreting the same in an active voice is equally important.
Would this diminish traditional websites that are in use today?
Not one bit! They will remain as they are, plus will include content that can be easily readable and ideal for TTS on Voice interface applications. This also implies that the content would, therefore, be ideal if –
- The content is reproduced in a conversational style
- Use more natural language/speech in content
- Structure your text using Speak able
- Make certain specifics as verbose as possible. Think of ways on how a user would ask a specific question
Voice Tech is at its infancy and now is the time for you to dive deep in it if you wish to stay ahead in this game. Voice searches enabled on devices that use Artificial intelligence. For instance, the Echo is enabled by Alexa (AI brain of Echo). Devices built on AI tend to replicate intelligence and intuition.
These devices are learning and evolving continuously by feeding on data across numerous platforms. This will ultimately help predict and recommend what a user might need in future effectively!