Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: A method and system for reporting data from a spoken dialog service is disclosed. The method comprises extracting data regarding user dialogs using a dialog logging module in the spoken dialog service, analyzing the data to identify trends and reporting the trends. The data may be presented in a visual form for easier consumption. The method may also relate to identifying data within the control or outside the control of a service provider that is used to adjust the spoken dialog service to maximize customer retention.

Abstract: Disclosed is a web server that includes a headlines module for automatically generating headlines based on data retrieved from a network (e.g., World Wide Web). The web server also includes an interactive agent for generating responses to inquiries relating to the headlines based on the data.

Abstract: A method and system for reporting data from a spoken dialog service is disclosed. The method comprises extracting data regarding user dialogs using a dialog logging module in the spoken dialog service, analyzing the data to identify trends and reporting the trends. The data may be presented in a visual form for easier consumption. The method may also relate to identifying data within the control or outside the control of a service provider that is used to adjust the spoken dialog service to maximize customer retention.

Abstract: A method and system for reporting data from a spoken dialog service is disclosed. The method comprises extracting data regarding user dialogs using a dialog logging module in the spoken dialog service, analyzing the data to identify trends and reporting the trends. The data may be presented in a visual form for easier consumption. The method may also relate to identifying data within the control or outside the control of a service provider that is used to adjust the spoken dialog service to maximize customer retention.

Abstract: Embodiments of the present invention relate to a method and system for augmenting a training database of an automated language-understanding system. In one embodiment, a training example in a first language is received from the training database. The first language-training example is translated to a second language output. The second language output is translated to a first variant of the first language-training example. An action pair including the first variant of the first language-training example and an action command associated with the first language-training example is stored in an augmented training database.

Abstract: Embodiments of the invention relate to a system and method for providing speech-enabled application programs. The speech-enabled programs automatically execute requests input by users. One or more natural language variants may be mapped with at least one natural language exemplar. The natural language exemplar may correspond to a typical way to express a request relevant to the speech-enabled application program. The natural language variant may correspond to an alternative way of expressing the same request. A recognized input string is received and a prospective variant that most resembles the received recognized input string is selected from the natural language variants. The natural language exemplar mapped to the prospective variant is identified. An action instruction associated with the identified natural language exemplar is executed to fulfill the user's request.

Abstract: Embodiments of the present invention relate to a method and system for augmenting a training database of an automated language-understanding system. In one embodiment, a training example in a first language is received from the training database. The first language-training example is translated to a second language output. The second language output is translated to a first variant of the first language-training example. An action pair including the first variant of the first language-training example and an action command associated with the first language-training example is stored in an augmented training database.

Abstract: Embodiments of the present invention relate to a method and system for augmenting a training database of an automated language-understanding system. In one embodiment, a training example in a first language is received from the training database. The first language-training example translated to a second language output. The second language output is translated to a first variant of the first language-training example. An action pair including the first variant of the first language-training example and an action command associated with the first language-training example is stored in an augmented training database.

Abstract: Embodiments of the present invention relate to a method and system for augmenting a training database of an automated language-understanding system. In one embodiment, a training example in a first language may be received from the training database. The first language-training example may be translated to a second language output. The second language output may be translated to a first variant of the first language-training example. An action pair including the first variant of the first language-training example and an action command associated with the first language-training example may be stored in an augmented training database.

Abstract: Embodiments of the present invention relate to a method and system for augmenting a training database of an automated language-understanding system. In one embodiment, a training example in a first language may be received from the training database. The first language-training example may be translated to a second language output. The second language output may be translated to a first variant of the first language-training example. An action pair including the first variant of the first language-training example and an action command associated with the first language-training example may be stored in an augmented training database.

Abstract: Embodiments of the invention relate to a system and method for providing speech-enabled application programs. The speech-enabled programs automatically execute requests input by users. One or more natural language variants may be mapped with at least one natural language exemplar. The natural language exemplar may correspond to a typical way to express a request relevant to the speech-enabled application program. The natural language variant may correspond to an alternative way of expressing the same request. A recognized input string is received and a prospective variant that most resembles the received recognized input string is selected from the natural language variants. The natural language exemplar mapped to the prospective variant is identified. An action instruction associated with the identified natural language exemplar is executed to fulfill the user's request.

Abstract: Embodiments of the invention relate to a system and method for providing speech-enabled application programs. The speech-enabled programs automatically execute requests input by users. One or more natural language variants may be mapped with at least one natural language exemplar. The natural language exemplar may correspond to a typical way to express a request relevant to the speech-enabled application program. The natural language variant may correspond to an alternative way of expressing the same request. A recognized input string is received and a prospective variant that most resembles the received recognized input string is selected from the natural language variants. The natural language exemplar mapped to the prospective variant is identified. An action instruction associated with the identified natural language exemplar is executed to fulfill the user's request.

Abstract: A method and apparatus for automatically constructing hierarchical transduction models for language translation is presented. The input to the construction process may be a database of examples each consisting of a transcribed speech utterance and its translation into another language. A translation pairing score is assigned (or computed) for translating a word in the source language into each of the possible translations it has in the target language. For each instance of the resulting training dataset, a head transducer may be constructed that translates the source string into the target string by splitting the source string into a source head word, the words preceding the source head word, and the words following the source head word. This process may be performed recursively to generate a set of transducer fragments. The transducer fragments may form a statistical head transducer model. The head transducer translation model may then be input into a transduction search module.