Koninklijke Philips Corporation N.v.

Nuance Communications, Inc.

Dictaphone Corporation.

Marc Helbing

Philip Steven Newton

Christiaan Varekamp

Wiebe De Haan

Wilhelmus Hendrikus Alfonsus Bruls

Johan Cornelis Talstra

Vasanth Philomin

Christian Benien

Georgios Parlantzas

Klaus Reifenrath

Gerardus Wilhelmus Theodorus Van Der Heijden

Geradus Wilhelmus Theodorus Van Der Heijden

Three dimensional [3D] image data and auxiliary graphical data are combined for rendering on a 3D display () by detecting depth values occurring in the 3D image data, and setting auxiliary depth values for the auxiliary graphical data () adaptively in dependence of the detected depth values. The 3D image data and the auxiliary graphical data at the auxiliary depth value are combined based on the depth values of the 3D image data. First an area of attention () in the 3D image data is detected. A depth pattern for the area of attention is determined, and the auxiliary depth values are set in dependence of the depth pattern.

Method and apparatus for combining 3D image and graphical data

Three dimensional [3D] image data and auxiliary graphical data are combined for rendering on a 3D display by detecting depth values occurring in the 3D image data and setting auxiliary depth values for the auxiliary graphical data adaptively in dependence of the detected depth values. The 3D image data and the auxiliary graphical data at the auxiliary depth value are combined based on the depth values of the 3D image data. First an area of attention in the 3D image data is detected. A depth pattern for the area of attention is determined, and the auxiliary depth values are set in dependence of the depth pattern.

Combining 3D image and graphical data

A method of improving speech recognition includes receiving a plurality of recognized sentences from an automatic speech recognition (ASR) engine, each of the plurality of the recognized sentences including a plurality of information items. A confirmation is also receive that a value of an information item of the plurality of information items has been misrecognized or recognized. If the value has been misrecognized, each of the plurality of sentences are deleted that include the value of the information item that was misrecognized. If the value has been recognized, each of the plurality of sentences that do not include the value of the information item is deleted. The remaining sentences are transmitted to a dialog manager module.

Algorithm for n-best ASR result processing to improve accuracy

A method for improving speech recognition accuracy includes utilizing skiplists or lists of values that cannot occur because of improbability or impossibility. A table or list is stored in a dialog manager module. The table includes a plurality of information items and a corresponding list of improbable values for each of the plurality of information items. A plurality of recognized ordered interpretations is received from an automatic speech recognition (ASR) engine. Each of the plurality of recognized ordered interpretations each includes a number of information items. A value of one or more of the received information items for a first recognized ordered interpretation is compared to a table to determine if the value of the one of the received information items matches any of the list of improbable values for the corresponding information item.

Avoiding repeated misunderstandings in spoken dialog system

A device improves speech recognition accuracy by utilizing an external knowledge source. The device receives a speech recognition result from an automatic speech recognition (ASR) engine, the speech recognition result including a plurality of ordered interpretations, wherein each of the ordered interpretations includes a plurality of information items. The device analyzes and filters the plurality of interpretations using an external knowledge source to create a filtered plurality of ordered interpretations. The device stores the filtered plurality of ordered interpretations to a memory. The device transmits the filtered plurality of ordered interpretations to a dialog manager module to create a textual output. Alternatively, the dialog manager module retrieves the filtered plurality of ordered interpretations from a memory.

Incorporation of external knowledge in multimodal dialog systems

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Aachen, Germany

Marc Helbing