Amazon Technologies, Inc.

Ameya Agaskar

Sumit Garg

Christopher Evans

Zhengping Jin

Mohammad Edris Qarghah

Aaron Challenner

Ahmed Abdelal

Sai Kiran Venkata Subramanya Rupanagudi

Nagaraj Mahajan

Terrence Yu

David McGuire

Siddharth Agrawal

Pavas Kant

Nathaniel White

Yuxuan Hao

Described herein is a system for performing watermark detection using multiple time shifts to increase a resolution of watermark detection. Instead of decoding blocks of successive audio frames (e.g., 10 ms of audio) using a single watermark decoder, watermark verification can be performed by decoding overlapping frame shifts using multiple decoders in parallel, thereby increasing a chance that one of the watermark decoders will be synchronized with the embedded audio watermark. For example, watermark verification may split audio data into parallel streams and decode using two decoders (e.g., 2× shifts-per-frame), four decoders (e.g., 4× shifts-per-frame), or the like. Increasing resolution by performing overlapping detection increases an accuracy of the watermark detection without changing the embedded audio watermark.

Decoding audio watermarks using time shifts

Described herein is a system for encoding audio watermarks with time extensions to enable enhanced watermark detection. An extended audio watermark may include an existing audio watermark and a watermark extension, enabling backwards compatibility with existing watermark detection while also enabling enhanced watermark detection with increased accuracy. For example, embedding the extended acoustic watermark enables (i) limited devices to perform watermark detection to detect the existing audio watermark, and (ii) improved devices to perform enhanced watermark detection to detect the extended audio watermark. As the extended audio watermark has a longer time duration than the existing audio watermark, an accuracy of performing enhanced watermark detection is increased relative to detecting the existing audio watermark alone.

Extended audio watermarks

Described herein is a system for encoding audio watermarks with frequency extensions to enable enhanced watermark detection. An extended audio watermark may include an existing audio watermark and a duplicate audio watermark, enabling backwards compatibility with existing watermark detection while also enabling enhanced watermark detection with increased accuracy. For example, embedding the extended audio watermark enables (i) limited devices to perform watermark detection to detect the existing audio watermark, and (ii) improved devices to perform enhanced watermark detection to detect the extended audio watermark. As the extended audio watermark includes redundancy in the form of duplicate audio watermark(s), an accuracy of performing enhanced watermark detection is increased relative to detecting the existing audio watermark alone.

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

Described herein is a system for embedding audio watermarks. To improve performance without a user perceiving the audio watermark, a system embeds audio watermarks in audio data using scaling factors that are calculated based on a spectral masking level for each frame of the audio data. The scaling factors may vary over time and correspond to an amplitude of the audio watermark across a series of watermark frames. The system processes the audio data to determine a spectral mask, which represents an amount of energy perceived in a first frequency range that is caused by energy represented in neighboring frequency ranges. By selecting scaling factor values that keep an amplitude of the audio watermark below the threshold indicated by the spectral mask, the system may embed the audio watermark in the first audio data without the audio watermark being audible to the user.

Audio watermarking

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Bedford, MA, United States of America

Ameya Agaskar