Abstract: There is disclosed a method and system for engaging in a dialog with a user. The dialog system may receive input from the user. The dialog system may determine text for responding to the user. The dialog system may determine products to recommend to the user. The dialog system may generate a summary of reviews corresponding to the products. A response may be output to the user based on the text for responding to the user, the products to recommend to the user, and the summary of reviews corresponding to the products.

Abstract: There is disclosed a method and system for engaging in a dialog with a user. The dialog system may receive input from the user. The dialog system may determine text for responding to the user. The dialog system may determine products to recommend to the user. The dialog system may generate a summary of reviews corresponding to the products. A response may be output to the user based on the text for responding to the user, the products to recommend to the user, and the summary of reviews corresponding to the products.

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 having little or no in-domain manually transcribed 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. 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: 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 having little or no in-domain manually transcribed 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. When the adaptation training data satisfies a pre-determined adaptation criteria, the semantic classification system is automatically retrained based on the adaptation training data.