Nuance Communications, Inc.

Jan Curin

Jan Kleindienst

Martin Labsky

Tomas Macek

Holger Quast

David Nahamoo

William F Ganong, Iii

Garrett Weinberg

Lars Koenig

Simona Gandrabur

Eric Buist

Jiri Havelka

Lars Köenig

In some embodiments, a system is provided comprising at least one processor programmed to process an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a plurality of semantic entities identified from the at least one input text, and the plurality of semantic entities occur in a common context within the at least one input text. The at least one processor may be further programmed to use statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns.

Systems and methods for learning semantic patterns from textual data

Techniques for error correction using a history list comprising at least one misrecognition and correction information associated with each of the at least one misrecognitions indicating how a user corrected the associated misrecognition. The techniques include converting data input from a user to generate a text segment, determining whether at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, if the at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, obtaining the correction information associated with the at least one misrecognition, and correcting the at least a portion of the text segment based, at least in part, on the correction information.

Methods and apparatus for correcting recognition errors

An automotive text display arrangement is described which includes a driver text display positioned directly in front of an automobile driver and displaying a limited amount of text to the driver without impairing forward visual attention of the driver. The arrangement may include a boundary insertion mode wherein when the active text position is an active text boundary, new text is inserted between the text items separated by the active text boundary, and when the active text position is an active text item, new text replaces the active text item. In addition or alternatively, there may be a multifunctional text control knob offering multiple different user movements, each performing an associated text processing function.

Text browsing, editing and correction methods for automotive applications

A textual message processing system and method are described for use in a mobile environment. A user messaging application processes at least one user textual message during a user messaging session. A semantic annotation module identifies one or more semantically salient terms in the user textual message, and annotates the user textual message with annotation terms having a low semantic distance to the semantically salient terms. A user message history stores the annotated textual messages. The semantic annotation module may further annotate the user textual message with situational meta-data characterizing the user textual message. There may be a message search module for using one or more keywords to search the user message history including the annotation terms, and identifying as a search match any annotated textual messages within a semantic distance threshold of the one or more keywords.

Concept search and semantic annotation for mobile messaging

Techniques for presenting data input as a plurality of data chunks including a first data chunk and a second data chunk. The techniques include converting the plurality of data chunks to a textual representation comprising a plurality of text chunks including a first text chunk corresponding to the first data chunk and a second text chunk corresponding to the second data chunk, respectively, and providing a presentation of at least part of the textual representation such that the first text chunk is presented differently than the second text chunk to, when presented, assist a user in proofing the textual representation.

Methods and apparatus for proofing of a text input

An automatic conversational system has multiple computer-implemented dialogue components for conducting an automated dialogue process with a human user. A user client delivers dialogue output prompts to the human user and receives dialogue input responses from the human user including speech inputs. An automatic speech recognition engine processes the speech inputs to determine corresponding sequences of representative text words. A natural language understanding (NLU) processing arrangement processes the dialogue input responses and the text words to determine corresponding semantic interpretations. The NLU processing arrangement includes an anaphora processor that accesses different information sources characterizing dialogue context, linguistic features, and NLU features to identify unresolved anaphora in the text words needing resolution in order to determine a semantic interpretation. A dialogue manager manages the dialogue process with the human user based on the semantic interpretations.

Anaphora resolution using linguisitic cues, dialogue context, and general knowledge

A text message processing arrangement is described for use in a mobile environment. A mobile messaging application processes user text messages during a user messaging session. A user state model reflects situational parameters to characterize user cognitive load. A functionality control module adjusts functional performance of the mobile messaging application based on the user state model.

Situation-aware message presentation for automotive messaging

Techniques for disambiguating at least one text segment from at least one acoustically similar word and/or phrase. The techniques include identifying at least one text segment, in a textual representation having a plurality of text segments, having at least one acoustically similar word and/or phrase which has a different spelling, annotating the textual representation with disambiguating information to help disambiguate the at least one text segment from the at least one acoustically similar word and/or phrase, and synthesizing a speech signal, at least in part, by performing text-to-speech synthesis on at least a portion of the textual representation that includes the at least one text segment, wherein the speech signal includes speech corresponding to the disambiguating information located proximate the portion of the speech signal corresponding to the at least one text segment.

Growing community of inventors

Prague, Czechia

Jan Curin