公开(公告)号：US20160189037A1

公开(公告)日：2016-06-30

申请号：US14582235

申请日：2014-12-24

Applicant: Intel Corporation

Inventor： Oren Pereg ,  Moshe Wasserblat ,  Michel Assayag ,  Alexander Sivak ,  Saurav Sahay ,  Junaith Ahemed Shahabdeen

IPC: G06N5/04 ,  G06N7/00 ,  G06N99/00

CPC classification number: G06N5/04 ,  G06N7/005 ,  G06N20/00

Abstract: One embodiment provides an apparatus. The apparatus includes a processor; at least one peripheral device coupled to the processor; a memory coupled to the processor; a generic sentiment model and a first domain training corpus stored in memory; and a hybrid sentiment analyzer logic stored in memory and to execute on the processor. The hybrid sentiment analyzer logic includes a sentiment lexicon generator logic to generate a domain sentiment lexicon based, at least in part, on the first domain training corpus and to store the domain sentiment lexicon in memory, a lexicon-based sentiment classifier logic to generate an annotated training corpus unsupervisedly, based, at least in part, on the domain sentiment lexicon and to store the annotated training corpus in memory, and a model-based sentiment adaptor logic to adapt the generic sentiment model based, at least in part, on the annotated training corpus to generate an adapted sentiment model and to store the adapted sentiment model in memory.

Abstract translation: 一个实施例提供了一种装置。 该装置包括处理器; 耦合到所述处理器的至少一个外围设备; 耦合到所述处理器的存储器; 通用情绪模型和存储在记忆体中的第一域训练语料库; 以及存储在存储器中并在处理器上执行的混合情绪分析器逻辑。 混合情绪分析器逻辑包括情感词典生成器逻辑，用于至少部分地基于第一域训练语料库生成域信息词典，并将域信息词典存储在存储器中，基于词典的情绪分类器逻辑，以生成 至少部分地基于领域情绪词典并且将注释的训练语料库存储在记忆体中，以及基于模型的情绪适配器逻辑，以至少部分地基于模型的情感适配器逻辑来适应通用情绪模型， 注释的训练语料库以产生适应的情绪模型并将适应的情绪模型存储在存储器中。

公开(公告)号：US20220101096A1

公开(公告)日：2022-03-31

申请号：US17549645

申请日：2021-12-13

Applicant: Intel Corporation

Inventor： Gadi Singer ,  Nagib Hakim ,  Phillip Howard ,  Daniel Korat ,  Vasudev Lal ,  Arden Ma ,  Erik Norden ,  Ze'ev Rivlin ,  Ana Paula Quirino Simoes ,  Oren Pereg ,  Moshe Wasserblat

IPC: G06N3/04 ,  G06N5/02 ,  G06N5/04 ,  G06K9/62 ,  G06F11/34

Abstract: Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory are disclosed. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least estimate a first information extraction cost corresponding to retrieval of information from a local knowledge base, estimate a second information extraction cost corresponding retrieval of information from a remote knowledge base, select an information source based on the first and second estimated information extraction costs, query the selected information source, in response to determining that the selected information source was an external information source, store the queried information in the local knowledge base, organize the stored information in the local knowledge base, and return the queried information.

公开(公告)号：US20200243069A1

公开(公告)日：2020-07-30

申请号：US16650161

申请日：2017-11-15

Applicant: INTEL CORPORATION

Inventor： Gabriel Amores ,  Guillermo Perez ,  Moshe Wasserblat ,  Michael Deisher ,  Loic Dufresne de Virel

IPC: G10L15/06 ,  G10L15/16 ,  G10L15/183

Abstract: An apparatus for speech model with personalization via ambient context harvesting, is described herein. The apparatus includes a microphone, context harvesting module, confidence module, and training module. The context harvesting module is to determine a context associated with the captured audio signals. A confidence module is to determine a confidence of the context as applied to the audio signals. A training module is to train a neural network in response to the confidence being above a predetermined threshold.

公开(公告)号：US09591349B2

公开(公告)日：2017-03-07

申请号：US14581548

申请日：2014-12-23

Applicant: Intel Corporation

Inventor： Michel Assayag ,  Shahar Taite ,  Moshe Wasserblat ,  Tomer Rider ,  Oren Pereg ,  Alexander Sivak

IPC: H04N21/431 ,  H04N21/258 ,  H04N21/45 ,  H04N21/414 ,  H04N21/61 ,  H04N21/81 ,  H04N21/4223 ,  H04N21/4722 ,  H04N21/658

CPC classification number: H04N21/4312 ,  H04N21/25841 ,  H04N21/41407 ,  H04N21/4223 ,  H04N21/4524 ,  H04N21/4722 ,  H04N21/6131 ,  H04N21/6181 ,  H04N21/6582 ,  H04N21/8133

Abstract: 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.

Abstract translation: 这里描述了用于在移动设备上提供可重新定位的视频显示以模拟用户控制的双筒望远镜的效果的各种系统和方法。 在一个示例中，一个或多个高分辨率视频源（例如UltraHD摄像机）获得无线广播到移动设备的视频。 移动设备相对于移动设备的视野内的场景，基于观众的移动设备的大致位置处理广播。 移动设备的位置可以从网络监控，摄像机输入，对象识别等的组合中导出。 因此，观众可以从观众的移动装置上显示的外部视频源获得场景的虚拟放大率。