Partial automation of text chat conversations
AssigneeVerint Americas Inc.
InventorIan Beaver
Life of this patent
Estimating the term…
Abstract
To allow the human customer service agents to specialize in the instances where human service is preferred, but to scale to the volume of large call centers, systems and methods are provided in which human agents and intelligent virtual assistants (IVAs) co-handle a conversation with a customer. IVAs handle simple or moderate tasks, and human agents are used for those tasks that require or would benefit from human compassion or special handling. Instead of starting the conversation with an IVA and then escalating or passing control of the conversation to a human to complete, the IVAs and human agents work together on a conversation.
Claims20
A method for active learning for partially automating a text chat conversation, the method comprising:
- receiving a text conversation between a user computing device and a corresponding agent computer device, herein a sample;
- determining an intent of the sample using a trained language model, wherein in response to the trained language model finding the sample intent indeterminate:
- requesting a reviewer input to label the intent of the sample;
- adding the labeled sample to a labeled training set;
- and
- retraining the trained language model on the labeled training set;
- and
- using the retrained language model in a text conversation between the user computing device and an Intelligent Virtual Assistant (IVA).
A system for active learning for partially automating a text chat conversation, the system comprising:
- an agent computing device with human agent text conversation capability and intelligent virtual assistant (IVA) text conversation ability;
- a natural language understanding (NLU) component configured to use a language model in a text conversation between a user computing device and an IVA;
- and
- an active learning engine configured to:
- requesting a reviewer input to label an unlabeled sample;
- add the labeled sample to a labeled training set;
- and
- retrain the trained language model on the labeled training set.
Dependencies are inferred from the claim text.