Amazon Technologies, Inc.

Daniel Robert Rashid

Naresh Narayanan

Colin Wills Wightman

Jason George McHugh

Tracy Dianne Schultz

Alexander David Rosen

Michal Maciej Bryc

Michael James Rodehorst

Peng Shao

Prasanna Srinivasan Venkatasubramanian

Systems and methods for determining that artificial commands, in excess of a threshold value, are detected by multiple voice activated electronic devices is described herein. In some embodiments, numerous voice activated electronic devices may send audio data representing a phrase to a backend system at a substantially same time. Text data representing the phrase, and counts for instances of that text data, may be generated. If the number of counts exceeds a predefined threshold, the backend system may cause any remaining response generation functionality that particular command that is in excess of the predefined threshold to be stopped, and those devices returned to a sleep state. In some embodiments, a sound profile unique to the phrase that caused the excess of the predefined threshold may be generated such that future instances of the same phrase may be recognized prior to text data being generated, conserving the backend system's resources.

Post-speech recognition request surplus detection and prevention

Systems and methods for generating sound profiles of artificial commands detected by multiple voice activated electronic devices is described herein. In some embodiments, numerous voice activated electronic devices may send audio data representing a phrase to a backend system at a substantially same time. Text data representing the phrase, and counts for instances of that text data, may be generated. If the number of counts exceeds a predefined threshold, the backend system may cause any remaining response generation functionality that particular command that is in excess of the predefined threshold to be stopped, and those devices returned to a sleep state. In some embodiments, a sound profile unique to the phrase that caused the excess of the predefined threshold may be generated such that future instances of the same phrase may be recognized prior to text data being generated, conserving the backend system's resources.

Sound profile generation based on speech recognition results exceeding a threshold

This disclosure describes systems, methods, and computer-readable media related to semantic processing of content for product identification. Content may be received from a user device. The content may be processed based at least in part on one or more content filters. At least a portion of the processed content may be analyzed with named-entity recognition to identify one or more product references. A confidence score associated with each of the one or more product references may be calculated. Data associated with the one or more product references may be obtained. The data associated with the one or more product references may be transmitted for presentation on the user device.

Semantic processing of content for product identification

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Seattle, WA, United States of America

Daniel Robert Rashid