Systems and methods for discovering artists

A musician discovery system is provided. The musician discovery system includes a first interface for displaying a plurality of musicians organized according to a musical characteristic. The system includes a second interface for presenting multimedia information about a first musician from the plurality of musicians displayed on the first interface. The system includes means for comparing a second plurality of musicians with the first musician using the multimedia information presented on the second interface about the first musician. Furthermore, the system includes a third interface for recommending a second musician from the second plurality of musicians based on the comparing means.

FIELD OF THE INVENTION

The technology generally relates to systems and methods for exploring music and discovering artists. An artist can be understood as a musician within the context of the present invention.

BACKGROUND OF THE INVENTION

Conventional metrics for gauging the popularity of an artist include CD sales and radio plays. However, these metrics are less useful for discovering new, up-and-coming artists. This is because conventional metrics do not take into account of other platforms used by fans today to explore music, such as, for example, social media networks or video streaming websites.

Hence, systems and methods are needed to provide comprehensive, real-time tracking and analysis of up-and-coming artists. In addition, a discovery tool is needed for finding new artists and new music.

SUMMARY OF THE INVENTION

The invention, in various embodiments, features systems and methods for exploring music and discovering artists.

In one aspect, a musician discovery system is provided. The system includes a first interface for displaying multiple musicians organized according to a musical characteristic. The system also includes a second interface for presenting multimedia information about a first musician from the musicians displayed on the first interface. The system additionally includes means for comparing a second set of musicians with the first musician using the multimedia information presented on the second interface about the first musician. The system further includes a third interface for recommending a second musician from the second set of musicians based on the comparing means.

In another aspect, a computer-assisted method for discovering musicians is provided. The method includes selecting multiple musicians from a library database based on information supplied by a user via a computer interface. The method includes organizing the musicians according to at least one musical characteristic. The method also includes permitting the user to select a first musician from the multiple musicians and presenting multimedia information about the first musician to the user collected from a plurality of media sources in electrical communication with the library database. The method further includes comparing a second set of musicians from the library database with the first musician to determine their similarity or dissimilarity with the first musician and recommending a second musician from the second set of musicians to the user based on the comparing.

In other examples, any of the aspects above can include one or more of the following features. In some embodiments, the multiple musicians can be selected based on an input by a user. The input can be a musician name or a musical genre.

In some embodiments, the multiple musicians are ranked by the first interface according to the musical characteristic. The musical characteristic can be a popularity score and the first interface ranks the plurality of musicians according to their corresponding popularity scores. The popularity score can be weighted according to a genre type associated with each musician. In some embodiments, one or more musicians are selected for display from the multiple musicians if their popularity scores are above a threshold. In some embodiments, one or more musicians are selected for display from the multiple musicians if their popularity scores are below a first threshold and above a second threshold.

In some embodiments, a similarity score is assigned to each of the second set of musicians and the similarity scores are compared to a threshold. In some embodiments, the similarity score associated with the second musician selected from the second set of musicians can be higher than the threshold. In some embodiments, the similarity score associated with the second musician selected from the second set of musicians is lower than the threshold.

In some embodiments, the multimedia information about the first musician includes at least one of biography, song, photo, blog, video or tweet associated with the first musician. In some embodiments, the musician discovery system further includes a library database for storing the multimedia information corresponding to the multiple musicians. The library database can be in electrical communication with at least one of a music database, a website, a photo database, a search engine and a video database.

In some embodiments, the third interface recommends the second musician based on a feature of musical similarity or dissimilarity between the first and second musicians. In some embodiments, the third interface is further adapted to display a third set of musicians from the library database who share a feature of musical similarity or dissimilarity with the first musician. The third interface can also rank the third set of musicians according to their degrees of similarity of dissimilarity with the first musician.

In some embodiments, the musician discovery system further includes a fourth interface for providing advertisement related to the plurality of musicians.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1shows an exemplary online artist discovery interface100according to one embodiment of the technology. As illustrated, interface100includes input field102through which a user can supply text-based inputs to the interface. A user can enter the inputs in free form via field102or select them from a drop down menu associated with field102. Interface100is also configured to present a list of “most buzzed” artists106and a list of “up and coming” artists108. In addition, interface100comprises an advertisement region110for targeted advertising.

In one embodiment, “most buzzed” list106is configured to provide a list of artists who are familiar to music listeners. Interface100generates “most buzzed” list106by searching for artists in one or more libraries in communication with interface100and assigning a familiarity score to each of the artists found. Interface100can compute an artist's familiarity score using systems and methods described in application Ser. Nos. 12/101,013 and 12/100,966, incorporated herein by reference. Known methods for computing an artist's familiarity score include determining the number of reviews and posts published about the artist in a given time period, tracking media attention received by the artist on social media websites and measuring the artist's media presence through online sales, radio plays and online media references.

In certain embodiments, the libraries can be located on a web server in electronic communication with a user device from which interface100is displayed. The libraries can store metadata, web content, musical tracks, videos and photos associated with a plurality of artists. In certain embodiments, the web server may include search engines providing efficient searches of the libraries by artist names, track titles or album titles, for example. In certain embodiments, the web server includes processing modules to control the operation of interface100. Further details regarding network environment of the present technology is discussed below with reference toFIG. 4.

Interface100is adapted to populate “most buzzed” list106with only those artists whose familiarity scores are above a threshold. The threshold can be predetermined or dynamically selected and/or adjusted based on the number of results generated from the search. For instance, if too few “most buzzed” artists are identified based on the threshold, interface100is adapted to lower the threshold until a sufficient number of artists are found for display via “most buzzed” list106. In addition, interface100can order artists on “most buzzed” list106according to their familiarity scores. For example, an artist who is more familiar to listeners can be ranked higher on the lists than a less familiar artist.

In another embodiment, “most buzzed” list106is configured to provide a list of artists who are popular with music listeners. To generate such a list, interface100is adapted to compute a popularity score for each artist found from one or more libraries in communication with interface100. A popularity score can be computed by weighting the artist's familiarity score by a factor that accounts for the popularity of the artist. In certain embodiments, each familiarity score is weighted according to the artist's music sales figures or survey information about the artist. For example, the more revenue an artist generates based on his or her music, the higher the artist's popularity score is. In certain embodiments, each familiarity score is weighted according to a music genre type associated with the artist. For example, artists who are associated with a hip-pop genre are given a greater weight for ranking purposes than artists who are associated with a classical genre. In certain embodiments, each familiarity score is weighted according to the popularity of the artist among a certain listener demographic. For instance, those artists who are more popular with the 16 to 25 year-old listener demographic are assigned a greater weight than those who are less popular with the same demographic. Listener statistics such as age can be collected on an opt-in basis when, for instance, a listener accesses his or her personal account with the artist discovery system of the present technology. In certain embodiments, each familiarity score is weighted according to the reliability of the sources from which information about the popularity of the artist is collected. In certain embodiments, each familiarity score is weighted according to one or more music-related statistics collected within a specified time frame, such as the number of times an artist's videos had been played, the number of times an artist's name had been searched via interface100or any other search engines, the total air time associated with an artist, and the number of show appearances by an artist. In certain embodiments, each familiarity score is weighted according to certain tour-related statistics such as ticket sales generated from an artist's tour, the number of people who attended an artist's tour, and the number of cities on an artist's tour. In some embodiments the tour status, i.e., whether an artist is on tour, is used to weigh a familiarity score.

Interface100is adapted to display via “most buzzed” list106only those artists whose popularity scores are above a certain threshold. The threshold can be predetermined or dynamically selected and/or adjusted based on the number of results generated from the search.

In another embodiment, “most buzzed” list106is configured to provide a list of artists who are popular with listeners and who share similar musical qualities as those embodied by one or more terms supplied by a user to interface100. A user can supply information to interface100via any client terminals that are configured to display interface100. Exemplary client terminals are described below with reference toFIG. 4.

In operation, upon the user entering information via field102and clicking “explore” button104to submit the information, interface100is adapted to search for artists in one or more libraries in communication with interface100and assign a similarity score to each of the artists identified. Each similarity score reflects the degree of musical similarity between the artist and the input information. Exemplary inputs to search field102include one or more artist names, music track titles, music genres or a combination thereof. As one example, if a user enters the names of two artists in field102, the similarity score computed for a third artist reflects how musically similar the third artist is to both of the named artists. As another example, if a user enters the name of a first artist in conjunction with an album title associated with a second artist, the similarity score for a third artist reflects how musically similar the third artist is to the named artist and the named album. A similarity score and can be computed based on similarities in musical genre, tempo, rhythm, beats, melody, pitch, harmony, or timbre, for example. A similarity score can be computed based on the frequency two artists are mentioned together in media outlets such as blogs, news articles, tweets, etc. A similarity score can also be computed using the systems and methods described in application Ser. Nos. 12/101,013 and 12/100,966 incorporated herein by reference. Interface100is also adapted to compute a popularity score for each of the artists identified using any one of the popularity score determination means described above. Interface100is further adapted to populate “most buzzed” list106with only those artists whose similarity scores are above a first threshold and whose popularity scores are above a second threshold.

According to yet another embodiment, “most buzzed” list106is configured to provide a list of popular artists who possess musical qualities dissimilar to those embodied by one or more user-supplied inputs via field102. In one example, interface100populates “most buzzed” list106with only those artists whose similarity scores are below a first threshold and whose popularity scores are above a second threshold. In another example, interface100assigns a dissimilarity score to each of the artists searched and populates “most buzzed” list106with only those artists whose dissimilarity scores are above a first threshold and whose popularity scores are above a second threshold. An artist's dissimilarity score reflects the degree of dissimilarity between the artist and the user-supplied information. A dissimilarity score and can be computed based on differences in musical genre, tempo, rhythm, beats, melody, pitch, harmony, or timbre, for example. A dissimilarity score can also be computed using the systems and methods described in application Ser. Nos. 12/101,013 and 12/100,966.

According to another aspect of the technology, interface100is configured to display “up and coming” list108. In one embodiment, “up and coming” list108presents a list of artists who are currently not familiar to music listeners but are rising in familiarity. Interface100generates such “up and coming” list108by searching for artists in one or more libraries in communication with interface100and assigning a familiarity score to each artist identified. Interface100is adapted to populate “up and coming” list108with only those artists whose familiarity scores are below a first threshold but above a second threshold.

In another embodiment, “up and coming” list108is configured to display a list of artists who are currently not popular with music listeners but are rising in popularity. Interface100generates such “up and coming” list108by computing a popularity score for each of the artists identified from one or more libraries coupled to interface100. The popularity score of an artist can be determined by weighting the artist's familiarity score using any of the weighting methods described above. Interface100is adapted to populate “up and coming” list108with only those artists whose popularity scores are below a first threshold but above a second threshold.

In another embodiment, “up and coming” list108is configured to provide a list of up and coming artists who have similar musical qualities as those embodied by one or more input terms. To generate such a list, interface100assigns a similarity score to each of the artists identified from one or more libraries in communication with interface100. Interface100is also adapted to compute a popularity score for each of the artists. “Up and coming” list106presents only those artists whose similarity scores are above a first threshold and whose popularity scores are below a second threshold but above a third threshold.

In yet another embodiment, “up and coming” list108is configured to provide a list of up and coming artists who possess musical qualities dissimilar to those captured by one or more input terms. In one example, “up and coming” list108is configured to present those artists who have similarity scores below a first threshold and popularity scores below a second threshold but above a third threshold. In another example, “up and coming” list108is configured to present those artists who have dissimilarity scores above a first threshold and popularity scores below a second threshold but above a third threshold.

In some embodiments, artists who appear on each of “most buzzed” list106and “up and coming” list108can be additionally grouped by musical genres such as, for example, Indies, Metal, Country, etc. In some embodiments, “most buzzed” list106or “up and coming” list108provides a list of “most buzzed” or “up and coming” artists, respectively, associated with only one or more user-specified musical genres.

According to another aspect of the technology, for each artist who appears on “most buzzed” list106or “up and coming” list108, interface100is adapted to show certain representative information about the artist in region112. Region112can display a representative photo of the artist, a representative video of the artist, a familiarity ranking assigned to the artist, one or more songs by the artist representative of the artist's talent, or a combination thereof. In certain embodiments, region112is linked to or expands into artist information card200, as shown inFIG. 2, which will be described below in detail.

In another aspect, interface100includes advertisement region110that is configured to provide targeted advertisements based on content displayed in interface100. Advertisement region110can present advertisement related to one or more artists on “most buzzed” list106or “up and coming” list108. Advertisement region110can also present advertisement related to user input terms entered via field102so that advertisements are tailored to a user's interest. Exemplary advertisements can be on latest music tours, recent album releases or fashion attires popular among artists who are presented in interface100.

In some embodiments, artist discovery interface100can include a radio-playing element (not shown) configured to play music by at least one artist on “most buzzed” list106or “up and coming” list108. In some embodiments, based on an artist identified on either of the lists, the radio-playing element can play music by other artists who are similar or dissimilar in musical style as the identified artist.

FIGS. 2A-Fillustrates various embodiments of an artist information card200according to one aspect of the technology. In general, artist information card200is configured to present information about a particular artist collected from a plurality of media sources such as from a library, an online source, or a third-party database that contain multimedia content such as videos, music tracks, photos or metadata. In certain embodiments, the library is located on a web server in electronic communication with a user device from which card200is displayed. In certain embodiments, the web server includes processing modules to control the operation of card200. In certain embodiments, the web server collects information about a particular artist from third-party databases and websites for presentation via card200. Further details regarding network environment of the present technology is discussed below with reference toFIG. 5.

As shown inFIGS. 2A-F, artist information card200can include an “audio” tab206displaying a music play region, a “videos” tab202displaying a video display region, a “photos” tab204displaying a photo display region, a “tweets” tab212displaying a region, a “news” tab210displaying a news region, and a “bio” tab208displaying a biography region.

As shown inFIG. 2A, artist information card200includes music play region206that allows a user to play select tracks by the artist featured in the region112. Card200is adapted to retrieve the tracks from databases located on one or more web servers in communication with card200or from tracks posted online. The databases may be internal databases or third-party databases owned by music content providers such as Rhapsody™. Card200can select for presentation those tracks by the artist that are most representative of the artist's musical talent, most requested, most popular, or by any other selection criterion. Similarly, card200can order the tracks by their release date, their popularity, the number of times each track has been played via card200, or by any other ordering criterion. Music play region206is configured such that a user can browse titles of all available tracks associated with the artist before selecting the one he or she wants to play. In some embodiments, the music play region206can play music by other artists who have similar or dissimilar musical style as the featured artist.

As shown inFIG. 2B, artist information card200can include video display region202that allows a user to play videos about the artist featured in region112. Card200is adapted to retrieve the videos from databases located on one or more web servers in communication with card200or from videos posted online. Exemplary videos include music videos featuring the artist, interview videos with the artist, or third-party videos discussing the artist. Video display region202is configured such that a user can browse all the available videos about the artist before selecting the one he or she wants to view.

As shown inFIG. 2C, artist information card200can include photo display region204that allows a user to view photos of the featured artist. Card200is adapted to retrieve the photos from databases located on one or more web servers in communication with card200or from photos posted online. Photo display region204can be configured such that a user can browse thumbnail images of all available photos associated with the artist before selecting the one he or she wants to view in a larger size or better resolution.

As shown inFIG. 2D, artist information card200can further include region210for displaying latest postings about the artist supplied by the artist himself or by a third party. Such information can be obtained from twitter pages, blogs, facebook pages, myspace pages, chatrooms, or other social networking websites. Content in region210is updated in real-time or in near real-time. In certain instances, the artist himself can directly post to region210to provide tour dates, concert locations, greetings to the fans, etc. In certain instances, a user can post comments about the artist to region210. Information posted in region210can be sorted in chronological order as it first appears or in accordance with the reliability of the sources from which the information is collected.

As shown inFIG. 2E, artist information card200can include news region212for providing latest news published on the artist. Such information can be obtained from a magazine site or a database owned by a news reporting agency, for example.

As shown inFIG. 2F, artist information card200can also include an artist biography region208for displaying biographical information about the featured artist. Card200is adapted to retrieve the biographical information from databases located on one or more web servers in communication with card200or from online sources such as Wikipedia, gossip websites and news websites or from music data services such as the Rovi Corporation. In certain instances, the information presented about the artist can be sorted according to the reliability of the sources from which the information is collected. For instance, information gathered about the artist from personal interviews, artist blogs, or trusted sites such as Wikipedia can be more prominently displayed than information collected about the artist from a gossip website.

In some embodiments, the artist information card200includes a “share” option218that allows a user to send card200to another via email. “Share” option218can also allow the user to embed artist information card200into a third-party website as a web widget, i.e., a stand-alone application. This effectively allows the user to turn artist information card200into a dynamic web application sharable on one or more third-party websites. For example, upon clicking “share” option218, a user is presented with a list of third party websites such as Facebook, Twitter, etc. The user can then select one of the websites, such as Facebook, to embed the artist information card200so that it appears on his Facebook profile.

In some embodiments, artist information card200can generate a list of artists who have similar musical qualities as the artist featured in card200. A user can access the list by choosing “similar” option216, for example. An illustrative list of similar artists is shown inFIG. 4and will be described in detail below. In some embodiments, the artist information card200can include a “dissimilar” option (not shown), through which a user can access a list of artists who have dissimilar musical qualities as the featured artist.

In some embodiments, artist information card200includes a “favorite” option220. Upon a user selecting “favorite” option220, the artist featured in the card200is saved in a list of favorite artists associated with the user. In addition, the user can retrieve card200at any point in time by choosing the artist from his “favorite” list.

FIG. 3shows another embodiment of artist information card200. As illustrated, card200can include, in one display, the music play region206, the video display region202, the photo display region204, the region212, the news region210and the biography region208.

In some embodiments, artist information card200includes an advertisement region220adapted to provide customized advertisement based on the content displayed in card200. For example, advertisement region220can present advertisement about the artist's latest tour or upcoming album or singles releases. Advertisement region220can advertise albums or tracks that share similar musical qualities as the featured artist. Advertisement region220can also advertise goods or services the artist has talked about recently or products that have appeared with the artist. For example, advertisement region220can advertise clothes worn by the artist in a photo displayed in region204.

Artist information card200can be accessed from a variety of sources. In some embodiments, a user can access artist information card200from interface100via region112that is associated with either “most buzzed” list106or “up and coming” list108. For example, as shown inFIGS. 2A-F, region112can be expanded into an artist information card200. In some embodiments, a user can access artist information card200directly from interface100by entering information about a particular artist via field102of interface100. In some embodiments, the artist information card200can be made available via a third-party website or found from an online search or link.

For example, artist information card200can be implemented as a hover box, which is a Graphic User Interface (GUI) event that can be triggered when a user moves or hovers his cursor over a particular area of the GUI, such as over the name of an artist who appears on “most buzzed” list106or “up and coming” list108in artist discovery interface100or over a name mentioned in a third-party GUI. Artist information displayed in a hover box can be a portion of the information displayed in artist information card200or the entire content of artist information card200.

As another example, a user can embed artist information card200in a third-party web interface by using, for example, “share” option218as described above. Exemplary embeddable interfaces include blog postings, facebook entries, myspace pages, etc.

FIG. 4provides an exemplary interface300displaying a “similarity” list302. In one embodiment, “similarity” list302presents those artists who share similar musical qualities as an artist featured in artist information card200. In another embodiment, “similarity” list302presents those artists who possess musical qualities similar to those captured by terms supplied by a user via field102of interface100.

Interface300can generate “similarity” list302by first conducting a search for similar artists in one or more libraries in communication with interface300. In certain embodiments, the libraries are located on a web server in electronic communication with a user device from which interface300is displayed. In certain embodiments, the web server includes processing modules to control the operation of interface300. Further details regarding network environment of the present technology is discussed below with reference toFIG. 5.

Interface300is configured to assign a similarity score to each artist searched that reflects the degree of similarity between the artist and the searched term. A similarity score can be computed based on similarities in musical genre, tempo, rhythm, beats, melody, pitch, harmony, timbre or a combination thereof. A similarity score can also be computed using the systems and methods described in application Ser. Nos. 12/101,013 and 12/100,966. “Similarity” list302is adapted to present those artists whose similarity scores are above a select threshold. Interface300can order the artists who appear on “similarity” list302according to their similarity scores, with the artist having the highest score highest on the list and the artist with the lowest score lowest on the list, for example.

For each artist who appears on “similarity” list302, interface300is adapted to show certain representative information about the artist in region304. For instance, region304can display a representative photo of the artist, a representative video of the artist, a similarity ranking assigned to the artist, one or more songs by the artist or a combination thereof. In certain instances, region304can indicate how much an artist's similarity score has changed in comparison to an earlier time. The change can be represented as a percentage change or as a whole number indicating a change in position on list304. In certain instances, region304is linked to or expandable into artist information card200, described above with reference toFIG. 2. Hence, a user can drill down on each artist presented on “similarity” list304.

According to another aspect of the technology, interface300can generate a list of artists who share dissimilar musical qualities as an artist featured in artist information card200. In another embodiment, interface300can generate a list of dissimilar artists based on an input term supplied by a user via field102of interface100.

In one example, a “dissimilarity” list includes those artists whose similarity scores are below a select threshold. In another example, a “dissimilarity” list includes those artists whose dissimilarity scores are above a select threshold.

According to yet another aspect of the technology, interface300includes a targeted advertisement region306for presenting advertisements customized based on the content displayed in interface300. Advertisement region306can advertise goods or services related to at least one artist on list304. Advertisement region306can also advertise goods or services related to a common feature among all the artists. For example, advertisement region306can advertise an album by an artist who is not on the list, but is in the same musical genre as the artists listed.

In some embodiments, interface300can include a radio-playing element (not shown) configured to play music by at least one artist on “similarity” list302. In some embodiments, the radio-playing element can play music by at least one artist on a “dissimilarity” list (not shown) generated by the interface300.

FIG. 5provides an exemplary network environment400. Network environment400includes one or more clients402, an artist server404and a plurality of web servers406. Each of clients402, artist server404and web servers406is in mutual communication with network420.

Each of clients402can be a computing device operated by a user. A computing device as used herein refers to any device with a processor and memory that can execute instructions. Computing devices include, but are not limited to, personal computers, server computers, portable computers, laptop computers, personal players, personal digital assistants (PDAs), cellular telephones, e-mail clients, tablets, Internet Protocol televisions (IPTV) and game consoles. These computing devices can run one or more application programs and an operating system. Each client402can include a wired or wireless interface to network420. In certain embodiments, clients402are configured to display interfaces100,200or300to users of the artist discovery system as well as allow the users to interface with the system. In general, interfaces100,200and300are platform independent and can run on a variety of computing platforms.

Artist server404can include one or more libraries or storage modules for storing metadata, photos, musical tracks and videos associated with a plurality of artists. Metadata can take the form of parameters, lists or other data structures. Metadata can include numerical, text, pictorial and other information about an artist. Photos can be in form of TIF, PNG, JPG, GIF or any other photo file format. Musical tracks can be in the form of MP3, MIDI, WAV, WMA, or any other audio file format. Videos can be in the form of AVI, MPEG, FIV or any other video file format.

Artist server404can also include processing modules to control the operation of interfaces100,200and300. Artist server404can further include one or more search engines to enable efficient searches of the information stored in the libraries or storage modules. Searches can be conducted by artist names, album titles, track titles, or other musical characteristics.

In certain embodiments, artist server404is configured to access the internet via network420to search for pertinent artist information. In certain embodiments, artist server404communicates with a plurality of external web servers406via network420. These web servers can host third-party music content, photo content, video content or metadata about artists. In certain instances, artist server404includes algorithms designed to conduct targeted queries of information in servers406as well as on the internet.

In certain embodiments, library server404is adapted to search its libraries and storage modules for artist-related information and supply such information to interfaces100,200and300for display. In certain embodiments, library server404queries third-party servers406for artist-related information for presentation via interfaces100,200and300. In certain embodiments, library server404searches online content for artist information. In certain embodiments, library server404updates its own database with information obtained from external servers or from the internet.