Amazon Technologies, Inc.

Sai Kiran Venkata Subramanya Rupanagudi

Sumit Garg

Ahmed Abdelal

Nagaraj Mahajan

Gengshen Fu

Aaron Challenner

Ameya Agaskar

Yuriy Mishchenko

Terrence Yu

Cody Jacques

David McGuire

Siddharth Agrawal

Huitian Lei

Pavas Kant

Nathaniel White

Yuxuan Hao

A device is configured to detect multiple different wakewords. A device may operate a joint encoder that operates on audio data to determine encoded audio data. The device may operate multiple different decoders which process the encoded audio data to determine if a wakeword is detected. Each decoder may correspond to a different wakeword. The decoders may use fewer computing resources than the joint encoder, allowing for the device to more easily perform multiple wakeword processing. Enabling/disabling wakeword(s) may involve the reconfiguring of a wakeword detector to add/remove data for respective decoder(s).

Multiple wakeword detection

A system configured to perform content recognition using fingerprinting to recognize known media content. A device determines fingerprints based on decoded content data to be sent using a media interface component to an output component. Metadata related to the content/device/fingerprint may also be created. The fingerprints and metadata are sent by the device to a supporting system for orchestration and matching of the fingerprints to known media content.

Content recognition using fingerprinting

A system configured to perform content identification using fingerprinting to recognize known media content. The system may generate a reference database including reference fingerprints for each media content item to include in the content identification. In addition, the system may generate a hash table that associates individual frames of the reference fingerprints with identification information for corresponding media content items. When a device is playing media content, the system may perform content identification by generating query fingerprints representing the media content and comparing the query fingerprints to the reference database. For example, the system may match a query fingerprint to a reference fingerprint by identifying which of the reference fingerprints shares the most frames with the query fingerprint using the hash table. In addition, the system may use additional decision criteria to confirm a match, such as fine-grain matching or tracking successive fingerprints over time.

Content identification using fingerprinting

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Burien, WA, United States of America

Sai Kiran Venkata Subramanya Rupanagudi