In a world where customer experience is crucial to business success, the contact centre exists at the heart of every crucial business conversation. In the age of digital transformation, access to the right technology can make or break the success of the average contact centre, helping organisations to implement the best state-of-the-art solutions for customer care.
In July 2018, Google's Cloud team announced the arrival of Contact Center AI - a solution to help companies apply intelligent solutions to their contact centre offering. Now, a year later, the GCP is introducing a host of exciting new updates to the tech at the centre of Contact Center AI, particularly Cloud Speech-to-Text, and Dialogflow.
Enhancing the Value of Virtual Agents & Auto Speech Adaptation
One of the first updates introduced by Google's Contact Center AI this month appears with the speech recognition features of virtual agents. As virtual assistants continue to support today's employees in delivering stronger around-the-clock user experiences, they're becoming increasingly important to the modern contact centre. However, automated speech recognition struggles in noisy contact centre environments. Fortunately, Google is introducing a new feature to help virtual agents understand what customers need.
Auto Speech Adaptation is the new intelligent solution from Google that brings context to the customer conversation. Speech Adaptation describes the learning process that Google's virtual assistants use to get to the heart of the nature of a conversation. For instance, the Dialogflow agent might now that the context of a conversation is a customer ordering a burger. Because of that, the virtual bot would be able to understand that the customer probably meant "bun," not "run" or "fun."
Additionally, because an agent would understand that "mail" is a common word to use when discussing a return, the bot would be less likely to confuse the word with "male." The new Auto Speech Adaptation feature ensures that virtual agents can take all available information into account when processing conversations, leading to a 40% or higher increase in accuracy. Auto Speech Adaptation will be turned off by default, but admins can switch it on within the Dialogflow console.
Cloud Speech-to-Text Improvements
Another significant update that Google has made this month comes in the form of new Speech-to-Text baseline model improvements for phone-based virtual agents and IVRs. In April of last year, Google introduced new pre-build models for transcription of video and phone calls. In February this year, those models became generally available. Today, the models are more advanced than ever, with a 15% improved accuracy rate for US English. The introduction of speech adaptation can also help customers to achieve even greater accuracy levels.
Accurate transcriptions in the contact centre can make it easier for agents to respond to the requests and needs of today's customers. The updates improve the quality of transcription accuracy for human agents.
Additionally, developers in Cloud Speech to Text will typically use "Speech Context" parameters to provide additional information to that transcription. This process improves the agent's ability to recognise phrases common in a specific environment. Today, the manual speech adaptation tuning in the Speech to Text environment will be richer than ever, with new enhancements in the Dialogflow and Cloud Speech-to-Text APIs. Google has announced the arrival of a further "boost" feature that will allow developers to use the best possible speech adaptation strength to suit their use case. This should help to increase the likelihood of complex phrases being captured.