Media usage monitoring and measurement system and method

Abstract

Media monitoring and measurement systems and methods are disclosed. Some embodiments of the present invention provide a media measurement system and method that utilizes audience data to enhance content identifications. Some embodiments analyze media player log data to enhance content identification. Other embodiments of the present invention analyze sample sequence data to enhance content identifications. Other embodiments analyze sequence data to enhance content identification and / or to establish channel identification. Yet other embodiments provide a system and method in which sample construction and selection parameters are adjusted based upon identification results. Yet other embodiments provide a method in which play-altering activity of an audience member is deduced from content offset values of identifications corresponding to captured samples. Yet other embodiments provide a monitoring and measurement system in which a media monitoring device is adapted to receive a wireless or non-wireless audio signal from a media player, the audio signal also being received wirelessly by headphones of a user of the monitoring device.

Description

CROSS REFERENCE TO RELATED APPLICATIONS [0001] This application claims the benefit of U.S. provisional application No. 60 / 574,836 entitled “Open-Ended Device-Independent Media Usage Monitoring and Measurement System,” filed May 27, 2004.BACKGROUND OF THE INVENTION [0002] Traditional media measurement systems have focused on directly monitoring channels being utilized by audience members. However, as media consumption patterns have become more complex, channel-centric media measurement is inadequate for many purposes. It may be desirable to track usage of particular media content independent of channel. Furthermore, although “channel” identification in a traditional media measurement system may sometimes be limited to radio or television broadcast station, it is increasingly desirable to track usage of media across several types of media delivery vehicles including radio, television, CD, DVD, computer download, portable media players (e.g. MP3 players, iPod), and other vehicles. Furt...

AI Technical Summary

Benefits of technology

[0006] Some embodiments of the present invention provide a media measurement system and method that enhances recognition (e.g. in terms of accuracy or efficiency) of the content of a media sample by analyzing information exogenous to the sample. Some embodiments of the present invention provide a media measurement system and method that utilizes audience data to enhance content identifications. Some embodiments analyze media player log data to enhance content identification. Other embodiments of the present invention analyze sample sequence data to enhance content identifications. Other embodiments analyze sequence data to enhance content identification and / or to establish channel identification. Yet other embodiments provide a system and method in which sample construction and selection parameters are adjusted based upon identification results. Yet other embodiments provide a method in which play-altering activity of an audience member is deduced from content offset values of identifications corresponding to captured samples. Yet other embodiments provide a monitoring and measurement system in which a media monitoring device is adapted to receive a wireless or non-wireless audio signal from a media player, the audio signal also being received wirelessly by headphones of a user of the monitoring device.

Problems solved by technology

However, as media consumption patterns have become more complex, channel-centric media measurement is inadequate for many purposes.

Furthermore, with respect to tracking consumption of advertisements, it may be inadequate to simply track channel tuning, because, for example, an audience member may mute a broadcast during commercial periods.

Thus simply identifying a broadcast channel does not adequately track whether the audience member listened to a particular advertisement.

However, such systems are limited in that they can only track content that has been properly encoded.

Although such systems can be efficiently deployed in the context of song recognition, deploying such systems in the context of media measurement systems poses particular challenges.

Continuous searching against a large database of media content can be computationally intensive.

Furthermore, such systems, while increasingly robust, still return some erroneous results, particularly in high-noise environments.

Such opportunities have thus far been insufficiently exploited for the purpose of efficiently applying existing content recognition technologies in the media measurement context.

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