Intel Corporation

Alexander Sivak

Tomer Rider

Moshe Wasserblat

Shahar Taite

Oren Pereg

Michel Assayag

Generally, this disclosure provides systems, devices, methods and computer readable media for adaptation of language models and semantic tracking to improve automatic speech recognition (ASR). A system for recognizing phrases of speech from a conversation may include an ASR circuit configured to transcribe a user's speech to a first estimated text sequence, based on a generalized language model. The system may also include a language model matching circuit configured to analyze the first estimated text sequence to determine a context and to select a personalized language model (PLM), from a plurality of PLMs, based on that context. The ASR circuit may further be configured to re-transcribe the speech based on the selected PLM to generate a lattice of paths of estimated text sequences, wherein each of the paths of estimated text sequences comprise one or more words and an acoustic score associated with each of the words.

Dynamic adaptation of language models and semantic tracking for automatic speech recognition

Various systems and methods for providing a repositionable video display on a mobile device, to emulate the effect of user-controlled binoculars, are described herein. In one example, one or more high resolution video sources (such as UltraHD video cameras) obtain video that is wirelessly broadcasted to mobile devices. The mobile device processes the broadcast based on the approximate location of the spectator's mobile device, relative to a scene within the field of view of the mobile device. The location of the mobile device may be derived from a combination of network monitoring, camera inputs, object recognition, and the like. Accordingly, the spectator can obtain a virtual magnification of a scene from an external video source displayed on the spectator's mobile device.

Growing community of inventors

Haifa, Israel

Alexander Sivak