Everyone knows that voice technologies have been experiencing exponential growth over the past few years. From the consumer gadgets we use in our homes and offices, to the solutions that are making customer interactions more efficient and seamless for businesses. To the extent that wholesale market changes are possible, just as mobile apps transformed the banking industry.
Indeed, recent stats show that as many as 25% of Google Android App searches were made by voice (US only). And Gartner predicts that 50% of analytics enquiries will be generated using search based on natural language processing (NLP) by 2020. It’s an exciting world to be in. But one of the key challenges of voice technology is effective implementation. There are lot of steps to take from the initial impetus to use voice technology to the eventual introduction of language tools. And for 70%, the client implementation need is around speed and accuracy combined.
To help our partners respond to the challenges that are being set for them by their customers, we organised a webinar to discuss our new implementation technology, Spitch Lingware Suite. Here’s what you missed if you couldn’t make it.
One of the key themes from the webinar was around the number of voice technologies there are, and how they can be implemented together to support the business goals of end users. For example, a voice conferencing business may have entirely different goals to a bank looking to be MiFID II compliant. Both can be supported by voice technology. The thing to answer is which technology and in what way?
Spitch Lingware Suite is the only NLP implementation platform that’s able to support the full cycle of development and implementation of voice technologies. It ensures partners that the entire spectrum of speech technologies can be effectively mobilised to address the specific business needs of clients – whether that’s voice and text data collection or annotation for the MiFID minded; or VB backend solutions for speaker verification and identification.
The technology can do this because it’s supported by a large, updated vocabulary, statistic semantic model (SSM) systems that analyse and categorise text, dialogue analysis that can monitor client satisfaction, and biometrics. Each of these performs a different role, allowing for multiple needs to be met at once by language programming solutions.
A core challenge of introducing any new technology for businesses is time to market. The longer that takes, the longer the customer must wait to see the benefit of it. Crucially, implementation can’t be rushed. If it is, the risk of errors grows and the provider will be looked to for quick, efficient fixes.
Only 17% of respondents to one of our pre-webinar polls said ROI and time to market were less relevant than accuracy; and only 13% said that a lack of customisation would be acceptable. As such, it’s absolutely necessary to balance time to market with accuracy, especially when voice technologies are so often used to ensure regulatory compliance and proof of customer service conversations.
Spitch Lingware Suite enables full implementation in a three-week period, from initial meeting to deployment. This is carried out in a three-stage process, beginning with voice and data collection, progressing through NLP engineering deployment (including speech recognition, semantic modelling and voice biometrics), and finally to telephone integration and a mobile software development kit.
There are numerous implementation scenarios where voice technologies are concerned. No one approach is suitable for all customers. To understand how different cases suit different needs, the webinar went onto explore three examples:
To listen to these use cases and learn more about the core topics explored in our webinar (including other opinion polls), watch the full webinar today.
Watch the Spitch Lingware Suite webinar
