Abstract: An automated method is described for developing an automated speech input semantic classification system such as a call routing system. A set of semantic classifications is defined for classification of input speech utterances, where each semantic classification represents a specific semantic classification of the speech input. The semantic classification system is trained from training data from training data substantially without manually transcribed in-domain training data, and then operated to assign input speech utterances to the defined semantic classifications. Adaptation training data based on input speech utterances is collected with manually assigned semantic labels from at least one source of already collected language data. When the adaptation training data satisfies a pre-determined adaptation criteria, the semantic classification system is automatically retrained based on the adaptation training data.

Abstract: A method for conducting a call between a caller and an interactive voice response (IVR) system, the caller using a device to conduct the call, the device configured to execute a virtual assistant, the method comprising using the virtual assistant to conduct the call at least in part by influencing the style of information provided to the caller during the call and/or the content of information passed between the device and the IVR system during the call.

Abstract: In a contact center, agents can be distracted and delayed from communicating with customers by searching for articles relevant to the customer's communication. A system automatically performing searches based on the customer's communication can therefore aid the agent. In an embodiment, a method of improving agent interaction with a user at a contact center includes determining, at a contact center, an intent of a portion of a received input from a user based on an established context of an application domain of the contact center. The method further includes mapping the determined intent to an element of an unstructured knowledge base stored in a memory. The method further includes presenting, to an agent at the contact center via a display, automated search results having the element of the one unstructured knowledge base. Therefore, the agent can quickly access search results relevant to the call and application domain.

Abstract: An automated method is described for developing an automated speech input semantic classification system such as a call routing system. A set of semantic classifications is defined for classification of input speech utterances, where each semantic classification represents a specific semantic classification of the speech input. The semantic classification system is trained from training data from training data substantially without manually transcribed in-domain training data, and then operated to assign input speech utterances to the defined semantic classifications. Adaptation training data based on input speech utterances is collected with manually assigned semantic labels from at least one source of already collected language data. When the adaptation training data satisfies a pre-determined adaptation criteria, the semantic classification system is automatically retrained based on the adaptation training data.

Abstract: A method for conducting a call between a caller and an interactive voice response (IVR) system, the caller using a device to conduct the call, the device configured to execute a virtual assistant, the method comprising using the virtual assistant to conduct the call at least in part by influencing the style of information provided to the caller during the call and/or the content of information passed between the device and the IVR system during the call.