Topic specific models for text formatting and speech recognition

US8041566B2 · kind B2 · utility

Assignee

• Nuance Communications Austria GmbH · AT

Inventors

• Jochen Peters · Norderstedt, DE
• Evgeny Matusov · Aachen, DE
• Carsten Meyer · Aachen, DE
• Dietrich Klakow · Aachen, DE

Key dates

• Filing date: Nov 12, 2004
• Grant date: Oct 18, 2011
• Expiry date: Dec 26, 2027

Classification

• Technology area (CPC G): Physics
• CPC primary: G10L15/32
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

The present invention relates to a method, a computer system and a computer program product for speech recognition and/or text formatting by making use of topic specific statistical models. A text document which may be obtained from a first speech recognition pass is subject to segmentation and to an assignment of topic specific models for each obtained section. Each model of the set of models provides statistic information about language model probabilities, about text processing or formatting rules, as e.g. the interpretation of commands for punctuation, formatting, text highlighting or of ambiguous text portions requiring specific formatting, as well as a specific vocabulary being characteristic for each section of the recognized text. Furthermore, other properties of a speech recognition and/or formatting system (such as e.g. settings for the speaking rate) may be encoded in the statistical models. The models themselves are generated on the basis of annotated training data and/or by manual coding. Based on the assignment of models to sections of text an improved speech recognition and/or text formatting procedure is performed.