Data processing: speech signal processing – linguistics – language – Speech signal processing – Application
Reexamination Certificate
2002-02-21
2004-06-08
Knepper, David D. (Department: 2654)
Data processing: speech signal processing, linguistics, language
Speech signal processing
Application
C704S231000
Reexamination Certificate
active
06748360
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a system for selling a product, and more specifically to systems and methods for selling a product containing audio content in which the audio content is automatically identified.
2. Description of Related Art
Audio content such as music is broadcast to listeners over various mediums that include radio, television, cable television, satellite television, and Internet web sites. When hearing a song from such a broadcast, a listener frequently does not know the artist and/or title of the song. If the listener enjoys the song and desires to purchase a recording of the song or a product containing the song (e.g., an album or video), the inability to identify the song currently playing prevents the listener from making the purchase. This leads to a missed sales opportunity to the detriment of the artist, all copyright holders, the product distributor, and the product retailer.
To identify a song that is heard, a listener currently must rely on some type of manual review that can only be successful if the chosen reviewer knows the identity of the song. For example, the listener could attempt to sing a portion of the song from memory for another person that the listener believes may know the identity of the song. Alternatively, the listener could record the song (or a portion of it) and play it back for another person to try to identify. Such identification techniques relying on manual review require the listener to find another person that is knowledgeable about such songs. Further, the listener's initial desire to purchase may wane by the time the song can be identified. Thus, there is a need for a system and method for allowing a listener to automatically identify audio content so that a product containing the audio content can be purchased.
One difficulty in developing a practical system for selling a product that provides automatic audio content identification is providing a mechanism for automatically identifying audio content. The identification of music from any source is not a trivial problem. Different encoding schemes will yield a different bit stream for the same song. Even if the same encoding scheme is used to encode the same song (i.e., sound recording) and create two digital audio files, the files will not necessarily match at the bit level.
Further, various effects can lead to differentiation of the bit stream even though the resulting sound differences as judged by human perception are negligible. These effects include: subtle differences in the overall frequency response of the recording system, digital to analog conversion effects, acoustic environmental effects such as reverb, and slight differences in the recording start time. Further, the bit stream that results from a recording of a song will vary depending on the type of audio source. For example, the bitstream for a song created by encoding the output of one stereo receiver will generally not match the bitstream for the same song created by encoding the output of another stereo receiver.
In addition, there are forms of noise and distortion that are quite audible to humans, but that do not impede our ability to recognize music. FM broadcasts and audio cassettes both have a lower bandwidth than CD recordings, and many of the MP3 files on the Internet are of relatively low quality. Furthermore, some recording systems may alter or distort the music, such as through slight time-stretching or time-compressing. In such cases, not only may the start and stop times be different, but the song duration may be different as well. All such differences may be barely noticeable to humans (if at all), but can foil many identification schemes.
There is a need for systems and methods that enable a listener to purchase unidentifiable audio content, such as by automatically and effectively identifying the audio content that was heard and then presenting one or more products containing the audio content.
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Abrams Steven
Fitch Blake G.
Germain Robert S.
Pitman Michael C.
August Casey P.
Bongini Stephen
Fleit Kain Gibbons Gutman Bongini & Bianco P.L.
Knepper David D.
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