Deutschetelekom Ag

Joachim Stegmann

Fred Runge

Martin Eckert

Wiebke Johannsen

Roman Englert

Markus Van Ballegooy

Frank Lonczewski

Gerhard Schroeder

Christian Weiss

Daria Frolova

Sigal Berman

Helman Stern

Thomas Scheerbarth

Felix Burkhardt

Frank Oberle

Johannes Minkwitz

Ingmar Kliche

Ralf Kirchherr

Bernd Lochschmidt

Jürgen Copenhaguen-Bormuth

Robert Hoffmann

Christian Müller

A method and system for adapting automated interactions that allows the interactive behavior of an automated system, or the nature of the interaction elements implemented thereon, to be adapted to properties and/or behaviors of users of such systems in order to enhance operating convenience. Interaction adaptation is performed with reference to user groups to which the users are allocated.

Method and system for adapting interactions

Gesture recognition system for remote controlling a TV is disclosed. The system comprises: (a) a webcam for capturing a video sequence of a user which is composed of video frames (b) a hand tracker for receiving the video sequence, and when a hand is determined within a frame of the video sequence, the hand tracker calculates the hand centroid; (c) a trajectory buffer for receiving plurality of the hand centroids as determined from plurality of frames respectively; (d) trajectory segmentation module for continuously inspecting the buffer for possible inclusion of relevant trajectories that relate to a hand gesture pattern, and whenever a relevant trajectory is detected, it extracts a respective trajectory segment, and conveys the segment into a gesture classifier; and (e) the gesture classifier for verifying whether the segment relates to a specific gesture command, and when affirmative, the gesture classifier transfers the respective command to the TV.

System and method for hand gesture recognition for remote control of an internet protocol TV

A method and a circuit arrangement for automatic voice activity detection on the basis of the wavelet transformation. A voice activity detection circuit or module ( ) is used to control a speech encoder ( ) and a speech decoder ( ), as well as a background noise encoder ( ) and a background noise decoder ( ) in order to perform source-controlled reduction of the mean transmission rate. After segmenting a speech signal, a wavelet transformation is computed for each frame, from which a set of parameters is determined, from which in turn a set of binary decision variables is calculated with the help of fixed thresholds in an arithmetic circuit ( ). The decision variables control a decision logic circuit ( ), whose result, after time smoothing in a time smoothing circuit ( ), provides the statement &ldquo;speech present/no speech&rdquo; for each frame. The circuit itself includes segmenting circuit ( ), a wavelet transformation circuit ( ), an arithmetic circuit for the energy values ( ), a pause detection circuit ( ), a circuit for detecting stationary states ( ), a first and a second background detector ( ), a downstream decision logic ( ), and the circuit ( ) for time smoothing, which provides the desired statement at its output ( ).

Voice activity detection method and device

A method and a device are described for classifying speech on the basis of the wavelet transformation for low-bit-rate speech coding processes. The method and the device permit a more robust classifier of speech signals for signal-matched control of speech coding processes in order to reduce the bit rate without affecting the speech quality or to increase the quality at the same bit rate. The method provides that, after segmenting the speech signal, a wavelet transformation is calculated for each frame, from which a set of parameters is determined with the help of adaptive thresholds. The parameters control a finite-state model, which subdivides the frames into shorter subframes if required, and classifies each subframe into one of several classes typical for speech coding. The speech signal is classified on the basis of the wavelet transformation for each time frame. Thus both a high time resolution (location of pulses) and frequency resolution (good mean values) can be achieved. This method and the classifier are therefore especially well suited for the control and selection of code books in a low-bit-rate speech coder. They also have a low sensitivity to background noise and low complexity.

Variable-subframe-length speech-coding classes derived from

Growing community of inventors

Darmstadt, Germany

Joachim Stegmann