It all started with bits and binary. Soon, algorithms came along which were eventually followed by the advanced OS. As research and innovation of devices made them capable of understanding and recognizing voice speech, tech enthusiasts were quick to catch up on that. Voice search or as programmers today call it voice recognition; is the ability of any software or machine to identify words and phrases in spoken language and convert them to a machine-readable format. The first breakthrough was observed in 1952, with Bell Laboratory’s Speech Recognition system that could understand the digits 0-9. This recognition device had the ability to understand speech with 97% accuracy which was a major breakthrough back then.
As people saw great potential with this technology, many giant companies put their best teams to champion this technology. IBM was one of them that came forth with a device that could also understand arithmetic commands. The Shoebox, as they called it, could not only understand speech inputs but could also recognize 16 English words including 10 digits and 6 arithmetic commands to run the operations. The wheel of evolution for this technology feels like it has probably spun too fast bringing us the AI such as Siri, Cortana and Google Assistant which as we know today are the pinnacle of voice search and assistance. Moreover, many tech experts predict 20 and 50 percent searches to be voice-initiated by 2020. That’s right, it is this year. Hence, it becomes very important for SEOs to start thinking about best practices and techniques for optimizing content for voice search & virtual assistants in their program.
Earning Featured Snippets for Your Website
The SEO for the latest interfaces is undoubtedly evolving with the increase in users as more people are being aware of these algorithms. This helps users get better opportunities for SEOs to initiate optimization using existing resources and get more efficient outcomes. A single answer is more successful for conventional tactics of traditional search where many of the responses Google provides come from featured snippets. However, you can map out a process for getting featured snippets for optimizing the content for your voice search which otherwise might become critical in voice search.
You need to identify common questions around your market sector and determine the most interesting related to your business from the lot. You can develop a set of closely related questions based on users’ interests to woo them. These will be your “target questions” that you will handpick for your audience. Finally, construct content addresses target and related questions in a single cohesive article.
Construct a Skill or an Action
What makes your voice assistant smart is how it responds to your questions and tasks. Every day, technology is pushing itself to make voice assistants and searches more human and versatile. Developers are creating all sorts of tasks and simple actions that can make the experience smarter, faster and more reliable. For instance, you can ask Siri or Alexa to search Quora or generally ask Google Assistant to give you an update with weather or cricket score. You can either build skills and actions manually or there are sites and services that will definitely make it easier to develop these search capabilities for non-coders too.
Google demonstrated the power of the next-generation voice module when they demonstrated how their voice assistant made an appointment for a haircut at a salon via phone call. Google’s CEO held the phone as hundreds of astonished audiences witnessed a voice assistant make a real phone call and book an appointment.
Developing Persona Models for Voice Apps
One of the key features of developing your personal voice models is it should sound more humanly and should possess a unique personality. Similar to how brands work hard to create a consistent image to give a unique customer experience, the actual voices spoken by virtual assistants should also have unique personalities. Computer-generated speech can have a gender variable with a little accent according to different parts of the world. People usually prefer voices that sound similar to them. Moreover, people will identify a computer-generated voice as more mechanical than the voice of the same personality type as their own.