Amazon Technologies, Inc.

Other

Matthew Joseph Cole

David Paul Ramos

Christopher Wayne Lockhart

Xulei Liu

Avnish Sikka

Sonjeev Jahagirdar

Yue Liu

Matthew Daniel Hart

Emilie Noelle McConville

Utkarsh Prateek

Ankur Datta

Bhavesh Anil Doshi

Rakesh Madhavan Nambiar

Junxiong Jia

Matias Omar Gregorio Benitez

Prashant Hegde

Laura Varnum Finney

Michael Vanne

Daniel Makoto Wilenson

A system and method for temporarily disabling keyword detection to avoid detection of machine-generated keywords. A local device may operate two keyword detectors. The first keyword detector operates on input audio data received by a microphone to capture keywords uttered by a user. In these instances, the keyword may be detected by the first detector and the audio data may be indicated for speech processing. The system may determine output audio data responsive to the input audio data. The local device may process the output audio data to determine that it also includes the keyword. The device may then disable the first keyword detector while the output audio data is played back by an audio speaker of the local device. Thus the local device may avoid detection of a keyword originating from the output audio. The first keyword detector may be reactivated after a time interval during which the keyword might be detectable in the output audio.

Multi-layer keyword detection

A system and method for temporarily disabling keyword detection to avoid detection of machine-generated keywords. A local device may operate two keyword detectors. The first keyword detector operates on input audio data received by a microphone to capture keywords uttered by a user. In these instances, the keyword may be detected by the first detector and the audio data may be transmitted to a remote device for processing. The remote device may generate output audio data to be sent to the local device. The local device may process the output audio data to determine that it also includes the keyword. The device may then disable the first keyword detector while the output audio data is played back by an audio speaker of the local device. Thus the local device may avoid detection of a keyword originating from the output audio. The first keyword detector may be reactivated after a time interval during which the keyword might be detectable in the output audio.

Multi-layer keyword detection for distributed voice communications

Disclosed are techniques for providing additional information for text in an image. In some implementations, a computing device receives an image including text. Optical character recognition (OCR) is performed on the image to produce recognized text. A word or a phrase is selected from the recognized text for providing additional information. One or more potential meanings of the selected word or phrase are determined. One of the potential meanings is selected based on other text in the image. A source of additional information corresponding to the selected meaning is selected for providing the additional information to a user's device.

Providing additional information for text in an image

A system and method for temporarily disabling keyword detection to avoid detection of machine-generated keywords. Audio data received for output by audio speakers is first captured by an effect component, such as an audio equalizer. The effect component may perform various operations including altering the audio data, copying the audio data and delaying the time in which the output audio is sent to the audio speakers. The effect component may generate a copy of the audio data and transmit or route the copy of the audio data to a secondary keyword detector via an audio channel, resulting in a further delay. The secondary detector may determine that the copy of the processed audio data includes a keyword that is likely to be output during a first time interval. The secondary detector may then transmit a signal to a primary keyword detector to disable keyword detection during the first time interval of the output audio.

Multi-layer keyword detection to avoid detection of keywords in output audio

Disclosed are techniques for merging optical character recognized (OCR'd) text from frames of image data. In some implementations, a device sends frames of image data to a server, where each frame includes at least a portion of a captured textual item. The server performs optical character recognition (OCR) on the image data of each frame. When OCR'd text from respective frames is returned to the device from the server, the device can perform matching operations on the text, for instance, using bounding boxes and/or edit distance processing. The device can merge any identified matches of OCR'd text from different frames. The device can then display the merged text with any corrections.

Merging optical character recognized text from frames of image data

Disclosed are techniques for recognizing text from one or more frames of image data using contextual information. In some implementations, image data including a captured textual item is processed to identify an entity in the image data. A context can be selected using the entity, where the context corresponds to a dictionary. Text in the captured textual item can be identified using the dictionary. The identified text can be output to a display device.

Recognizing text from frames of image data using contextual information

Embodiments of the subject technology provide for a hybrid OCR approach which combines server and device side processing that can offset disadvantages of performing OCR solely on the server side or the device side. More specifically, the subject technology utilizes image characteristics such as glyph details and image quality measurements to opportunistically schedule OCR processing on the mobile device and/or server. In this regard, text extracted by a 'faster' OCR engine (e.g., one with less latency) is displayed to a user, which is then updated by the result of a more accurate OCR engine (e.g., an OCR engine provided by the server). This approach allows factoring in additional parameters such as network latency and user preference for making scheduling decisions. Thus, the subject technology may provide significant gains in terms of reduced latency and increased accuracy by implementing one or more techniques associated with this hybrid OCR approach.

Hybrid optical character recognition

Various embodiments enable a computing device to incorporate frame selection or preprocessing techniques into a text recognition pipeline in an attempt to improve text recognition accuracy in various environments and situations. For example, a mobile computing device can capture images of text using a first camera, such as a rear-facing camera, while capturing images of the environment or a user with a second camera, such as a front-facing camera. Based on the images captured of the environment or user, one or more image preprocessing parameters can be determined and applied to the captured images in an attempt to improve text recognition accuracy.

Using a front-facing camera to improve OCR with a rear-facing camera

The recognition of text in an acquired image is improved by using general and type-specific heuristics that can determine the likelihood that a portion of the text is truncated at an edge of an image, frame, or screen. Truncated text can be filtered such that the user is not provided with an option to perform an undesirable task, such as to dial an incorrect number or connect to an incorrect Web address, based on recognizing an incomplete text string. The general and type-specific heuristics can be combined to improve confidence, and the image data can be pre-processed on the device before processing with an optical character recognition (OCR) engine. Multiple frames can be analyzed to attempt to recognize words or characters that might have been truncated in one or more of the frames.

Text recognition near an edge

Disclosed are techniques for providing additional information for text in an image. In some implementations, a computing device receives an image including text. Optical character recognition (OCR) is performed on the image to produce recognized text. One or more topics corresponding to the recognized text is determined. A word or a phrase is selected from the recognized text for providing additional information. One or more potential meanings of the selected word or phrase are determined. One of the potential meanings is selected using the one or more topics. A source of additional information corresponding to the selected meaning is selected for providing the additional information to a user's device.

Methods and systems are provided for modifying a firearm, including a kit for creating a modified handgun from first and second handguns. In one embodiment of the invention, a modified handgun is created which comprises a slide and barrel from a first handgun and a frame of a second handgun, using a kit comprising a dust cover insert, a replacement recoil spring and a replacement recoil spring guide.

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Arlington, MA, United States of America

Matthew Joseph Cole