International Business Machines Corporation

Nuance Communications, Inc.

Leiming R Qian

Vittorio R Castelli

Abraham P Ittycheriah

Robert T Ward

Jeffrey Scott McCarley

Jian-Ming Xu

Zareen S Syed

A method and system are provided for assisting users in a conversation. The method includes identifying concepts in the conversation. The method further includes linking identified concepts in the conversation by matching the identified concepts in the conversation to concepts in a knowledge base. The method also includes generating and displaying on the display device, one or more context dependent suggestions for the conversation based on attributes and values associated with the linked concepts in the knowledge base.

Automatic generation and display of context, missing attributes and suggestions for context dependent questions in response to a mouse hover on a displayed term

Techniques for translating and presenting text in a structured document are provided. A structured document including text to be translated is received. At least one portion of the text to be translated is translated into at least one representation of translated text of a specific language. The translation is carried out in accordance with a prioritization schedule. Further, the representation of translated text is provided by at least first and second servers, the first server independently providing the representation of translated text of a first quality and the second server independently providing the representation of translated text of a second quality, the first quality being different than the second quality. As the text is translated, the representation of translated text is presented immediately when available.

Prioritized incremental asynchronous machine translation of structured documents

An automated speech processing method, system and computer program product are disclosed. In one embodiment, a speech-to-text (STT) engine is used for converting an audio input to text data in a source language, and a machine translation (MT) engine is used for translating this text data to text data in a target language. In this embodiment, the text data in the target language is rendered on a display device, and different visualization schemes are applied to different parts of the rendered text data based on defined characteristics of the STT engine and the MT engine. In one embodiment, the defined characteristics include a defined confidence value representing the accuracy of the rendered text. For example, this confidence value may be based on both the accuracy of the conversion of the audio input and the accuracy of the translation of the text data to the target language.

Visualizing automatic speech recognition and machine translation output

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Ardsley, NY, United States of America

Leiming R Qian