Rules-based user preferences for stream switching in an internet radio player

Abstract

An internet radio player provides more personalized streaming audio content by assigning play amounts to different stream sources, and then playing streams from the different sources at a playback device for play times corresponding to the respective play amounts. The play time for a given stream is calculated as a user-defined percentage for the associated stream source multiplied by an expected listening period. The different stream sources can include different musical genres, news, sports, weather, or traffic. Play amounts are automatically adjusted based on user selection of the currently-playing stream source for increased or decreased play. A particular stream can also be played at a predetermined clock time, and the streams can further be ordered for play according to user preference. The present invention accordingly provides a richer listening experience than that attained by listening to a single internet radio stream, even if the single stream already reflects a user's preferences.

Description

BACKGROUND OF THE INVENTION[0001]1. Field of the Invention[0002]The present invention generally relates to the electronic transfer of consumer media, and more particularly to a system and method for providing internet users with a set of preferences for streaming audio media in order to enhance their listening experiences.[0003]2. Description of the Related Art[0004]Contemporary methods of listening to music often involve use of the Internet to obtain access to digital audio media. One way of listening to music which involves use of the Internet is downloading an audio file to a computer, phone, portable media player, etc., using a standard communications protocol such as file transfer protocol (FTP). When the audio file is downloaded, the file is essentially copied from its source (a remote server) to a local device which can then store the audio file. This means that a device such as a personal computer would have a digital copy of the audio file. With this audio file, a listener ...

AI Technical Summary

Benefits of technology

[0012]The play amounts can be automatically adjusted based on a user selection of one of the stream sources for increased or decreased play. A particular stream can also be played at a predetermined clock time, and the streams can further be ordered for play according to a user preference.

Problems solved by technology

When audio content is streamed over the Internet, a listener has real-time access to the audio reproduction, but access is much more limited when compared to downloading audio files.

Streamed audio data is transferred using a different protocol than those used for regular file downloads like FTP, so that listeners are not able to obtain an actual copy of the audio file.

This limitation is specifically designed to reduce the pirating of music.

Also, if a listener does not have access to the Internet then he or she has no way of streaming a given audio file, and a low-speed or unreliable connection will result in poor reproduction quality.

Conversely, a broadcast-type transmission in which only the station makes the musical selections is non-interactive.

The interactive or non-interactive nature of a stream can affect royalties or other fees that are required for transmission and performance of the streamed content.

Those internet radio stations which have only pre-programmed playlists lack the ability for any personalization or customizing.

If a listener is listening to a song on a pre-programmed playlist, there is no way for the listener to indicate their like or dislike for that song, so the playlist is unable to adapt to a user preference.

Those internet radio stations with playlists that are personalized based on a specific genre, artist, format, etc., are still somewhat restricting to listeners because oftentimes, although a listener might greatly like one specific song by a specific artist, they might not like other songs by that same artist or other versions (covers) of the song.

Similarly, if a listener likes a specific artist from a specific genre, they might not like all artists of that same genre.

However, recommendation engines have limitations too.

Oftentimes the algorithms which govern recommendation engines do not agree with user preferences.

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