SSML stands for Speech Synthesis Markup Language and it’s a markup language that helps standardize the way electronic or digitized devices communicate to humans. This markup language helps describe a collection of voice data and speech, and you can use it to enhance the customer experience to support how your bot processes your customer’s voice and speech.

However, it’s important to have insight on the technology behind SSML and know how to best use SSML to enhance your voice bot. Explore these SSML bot use cases and how you can create your own bot with this special text-to-speech markup language.

Why Create Your Bot Using SSML?

SSML

SSML has many use cases that make it ideal for enhancing interaction with humans, especially when creating chatbots or voice applications. For example, you can use SSML to improve the sound of your Alexa bot or to enhance the text-to-speech feature for a Cortana bot. This helps to personalize the experience for your customers.

Creating Your Bot with SSML

Designing a bot that leverages SSML doesn’t require an advanced computer science degree. You can apply a few best practices to ensure the success of your bot. Consider using these best practices for creating an SSML-powered bot:

  • Define the purpose of the bot. It’s important to understand the value your bot will provide your customer, and that’s why it’s critical to define it’s purpose. Outline how your bot will help your customer achieve his goals. For example, if the goal of the bot is to help translate foreign words, then write out how the services it provides will help your customer.
  • Choose your platform. Decide which platform will best serve your bot. For example, you can create your bot for Amazon’s Alexa devices, Google Home or Microsoft’s Cortana. You can also choose to create a bot that is supported by SSML across multiple devices to enhance the user experience with a cross-platform experience.
  • Design the conversation flow. Think about how your customer will interact with your voice bot. Your flow of conversation should occur naturally. This includes using the SSML appropriately to recognize inflections in the user’s voice to determine how to respond. If you are using SSML to make your bot sound less wooden, you can design cues that demonstrate these inflections. Also, anticipate the responses that your customers may have and use SSML to add personality that aligns with your brand’s voice.
  • Use Prototyping Tools. When you use prototyping tools, you can test the viability of your SSML-enabled bot. This makes it easy to identify any issues that may occur with the bot so you can fix it and avoid costly changes in your final product. You can use Botsociety to test out your bot and create a prototype that you can have users test for flaws before you make a large investment.

Enhance Interactions with SSML for Enhanced Engagement

Improving your customers’ experiences often calls for enhancing the value your voice bot or chat application delivers. You can get it done by using SSML to improve these interactions. Just put a few key strategies into action and implement SSML to support your voice application for engagement success.

 


Also published on Medium.

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Categories: Voice

Bianca Nieves

Digital Marketing Specialist at Botsociety