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Era - Enae Volare Mezzo Era - Enae Volare Mezzo Remix Era - Dont You Forget Era - Dont U Era - Dont U Edit Single 2 Era - Dont U A Capella Era - Dont Go Away Era - Divano Era - Devore Amante Tuesday 19 May Wednesday 20 May Thursday 21 May Friday 22 May Saturday 23 May Sunday 24 May Monday 25 May Tuesday 26 May Wednesday 27 May Thursday 28 May Friday 29 May Saturday 30 May Sunday 31 May Monday 1 June Tuesday 2 June Thursday 4 June Friday 5 June Saturday 6 June Sunday 7 June Monday 8 June Tuesday 9 June Monday 15 June Tuesday 16 June Wednesday 17 June Friday 19 June Saturday 20 June Sunday 21 June Monday 22 June Tuesday 23 June Wednesday 24 June Thursday 25 June Friday 26 June Saturday 27 June Sunday 28 June See System Requirements.

Available on PC Mobile device. Description The beautiful and professional Era of Microsoft formally known as 'Microsoft History' app gives you the information about Microsoft and its various products like Windows, Office, etc.

Show More. People also like. Microsoft Remote Desktop Rated 3. Office Lens Rated 4. Files Rated 4 out of 5 stars. OneDrive Rated 4 out of 5 stars. Windows Insider Rated 3 out of 5 stars. Firmware Update Check - Update assistant for legacy Win. This will remove all the songs from your queue.

Are you sure you want to continue? Clear currently playing song. Don't You Forget. If You Shout. Avemano Orchestral. The Champions. Omen Sore. Don't U. Misere Mani. In Fine. Ameno Remix. Mother Remix. This is sometimes referred to as vertical discovery. Unfortunately, the vast majority of playlists that are broadcast on terrestrial, Internet, or satellite radio tend to be highly genre-specific.

While this may be great for a listener that only wants a specific type of music, it represents a greatly reduced discovery ratio. Passive listeners who are unfamiliar with or who do not prefer these genres will rarely go there. The fact is that only a few songs from these smaller genres have significant crossover potential from both a genre and era standpoint. This is the approach now used by the partial download products offered by the major subscription services.

By contrast, the system of the preferred embodiment ranks songs individually for their crossover potential. In that manner, the system offers playlists at a certain rating level that are indifferent to genre or era.

This unique multi-genre crossover capability creates unprecedented variety, especially when the shuffle function is on. This, in turn, allows consumers to enjoy a much higher discovery ratio when they choose to do so.

While this approach is far too risky for traditional broadcasters, a fully-loaded MP3 player with a skip button removes the risk. The Source Selection Process Impacts Variety: As described above with respect to Filter 1 , all music bought or heard by consumers is first reviewed by one of five expert sources.

Which of these experts are selected from the thousands and thousands available will greatly impact the variety and quality of the playlist one recommends.

The playlists offered by the eight major Internet-based subscription services also focus on a narrow list of mostly major label artists. As a result, they all tend to play exactly the same songs packaged in slightly different ways. To address this problem, the satellite, and Internet-based platforms have begun to offer playlists directed at small non-label sources. However, just like their small genre lists, these are a harrowing experience for the average listener even with a time-shifted device.

By contrast, the system of the preferred embodiment includes only highly selected and rated music from a vast array of experts, including non-label music. Any given playlist will therefore include songs from a wide variety of non-label sources without requiring the consumer to search for them.

By selecting only artists with a major record contract, the traditional radio programmers automatically eliminate the same quality of artists before they have a contract. However, the system of the preferred embodiment and specifically the Remote Contributor Network includes an early detection capability that enables consumers to discover acts that are highly likely to get such a contract in the future.

Including Internet-Based Sources: For decades all five expert sources above were only required to listen to a fairly narrow list of artist names. Now, community sharing sites such as MySpace claim to offer websites of varying quality on over , bands. Meanwhile, the MusicNet database offers , artists. Clearly, this volume does not include much material that is of interest to the average passive listener, or the five expert sources they rely on to filter it.

Fortunately, MySpace, and another 60 or so of the music websites out there, now publish what these enormous populations are downloading and listening to on a daily basis.

However, it is believed that few programmers will admit using these new Internet-based sources today. This is because they have no way of systematically introducing this information into their traditional programming process.

By contrast, the system of the preferred embodiment has virtually automated the collection of this data into the system. This will provide professional programmers with a very powerful tool they lack today. Some of these concepts have been around for a long time while others are new initiatives.

There are also huge differences in the benefits these ideas offer and their potential for wide spread adoption. Promotional Pre-Loads: A number of device manufacturers have, in the past, pre-loaded a small and random collection of DRM-free songs in an effort to show off the devices or promote certain artists.

The music label companies have agreed to these one-off pre-loads in order to promote their own artists and in some cases, receive a small one-time per-device fee. None of these efforts have created any significant demand for the devices or the artists. Several years ago, PC makers also experimented with pre-loading small libraries of songs or selected playlists with similar results.

Recent efforts by Sansa include pre-loading specific albums or whole concerts to tiny memory sticks you can buy and insert in your portable music player i. Sansa Fuze. More importantly, there is no recurring revenue for the content provider PBM or the content owners labels, publishers, composers, artists.

In fact, their use may cannibalize subscription-based offerings. The benefits of pre-loading random collections of MP3 files are therefore, very limited. Pre-Loading Access to a Huge Catalog: New subscription services have recently been announced that provide access to a large unfiltered song universe by pre-loading it on an MP3 player or streaming it to a mobile phone.

However, for many years now, consumers have enjoyed free and relatively convenient access to a roughly 8,, unfiltered song universe on their PC through Limewire or similar illegal offerings. Not surprisingly, providing legal access to basically the same unfiltered song universe via iTunes, Rhapsody, Napster, and others, for a fee, is a low margin business with minor volume. In fact, recent estimates suggest that 1 billion songs are illegally shared per month. And, all of the illegal music is already portable by simply side-loading it to an iPod.

Without a properly programmed content solution, pre-loading unfiltered catalogs is unlikely to make much difference. For consumers, all that the pre-loading of this type accomplishes is temporarily allowing them to skip side-loading, from their PC, the music they want. This is probably an example of a technology solution looking for a problem. Again, consumers already have free access to this music on their PC and most people e. In fact, recent studies indicate that side-loading is preferred over various less known and more complicated wireless, mobile, and satellite solutions.

In short, side-loading is simple and it works. It will continue to improve in speed and simplicity. And again, side-loading illegal music to portable devices comes with no use restrictions. Some of these, such as Napster, Rhapsody, and Zune offer access to millions of unfiltered songs in addition to channel programming. They are also fully interactive.

All of internet radio operates under the Compulsory License with content owners. This severely limits or eliminates users' ability to replay, skip, save, or omit songs. Specifically, you are only able to skip 6 songs per hour, per station. There are two methods to choose a streaming station from any source. First, one can scroll through the 5, or so themed playlists available from a web platform such as Live The second method is to type in the names of one or more preferred artists or songs and listen to a list of songs with a similar digital fingerprint, in the order it is broadcast.

They spent many years and much money on a portable radio receiver able to receive satellite KU band and wireless signals. What they ended up with is certainly not free of the PC. To preload the device, the customer must first go to the Slacker website and construct 40 channels on the customer's PC.

The omissions can be performed wirelessly, but so what? With other products, the customer just tags them for omission and revises the list when the music is synced. Instead of wirelessly loading these to the device, Slacker side-loads them and mails it to the customer. In the end, all the customer can do is pre-load up to 40 small customer-created playlists onto a tiny portable device.

The first problem, of course, is that this is still Internet Radio operating under a Compulsory License. One must listen to the songs as broadcast, skipping is limited, unless you subscribe, and one can not search for individual songs or artists. If instead, entire playlists are simply side-loaded from any of the existing subscription platforms to the portable player, there are none of these restrictions.

The second problem is content management and programming. Like other preference-matching or recommendation services, the recommended songs come from a tiny selection of the 2,, songs available. This retrieval method, of course, varies according to the preferences entered on a PC and the number of songs in the system for which a fingerprint has been logged.

Or, the customer can skip all that and go with a themed playlist organized by the same programmers. Either way, the result is only 40 playlists to choose from on the customer's portable device.

Third, Slacker does not offer a pre-loaded song library, only a small collection of themed playlists which cannot be searched by artist or song. Fourth, Slacker pre-loads a tiny encrypted version of the songs found in 40 small playlists. Fifth, the Slacker device capacity is so small that the breadth and depth of their recommended playlists are actually smaller than what Satellite Radio provides. At approximately 70 songs, most of the playlists begin to recycle.

And the Premium subscription service is occasionally interrupted with in-house chatter just like satellite. Seventh, there is no organized channel guide like satellite. This is not convenient for most consumers and actually ends up limiting their discovery to the few artist and genres they already know about. In short, pre-loading internet radio stations is unlikely to replace current iPods, seriously hurt satellite radio in the car, or compete with the fully-loaded multi-channel solution offered by the embodiments described in earlier sections.

What follows is a summary of the key features of this unique approach to content management and pre-loading services. Identify the most popular 30, songs from an unfiltered 8,, song universe, dating back to , 2.

Classify and file these songs by multiple selection criteria into a well organized and uniform library, 3. Create pre-programmed music channels and allow any number of customer created playlists, 4. Sell a thoroughly tested PBM-authorized device that can be branded, 6.

Deliver the device, Express-Loaded, with a PBM library and music channels, within 72 hours to the customer's home, 7. Update the library and channels on a daily basis, 8. Provide customers access to MediaNet's 4,, song database from their PC, 9. Allow customers to customize PBM's pre-programmed music by omitting songs on-demand, Allow customers to skip, omit, replay, save, or purchase songs on-demand, without limitation, Provide a Crash and Loss protection program in the event the customer's subscription runs out, their PC crashes, or their device is lost.

Selecting the music, classifying and rating the songs, and preparing pre-programmed music channels would require a music expert several years. For this reason, a subscription-based licensing platform and state-of-the-art content management systems are notable features according to this embodiment.

The present embodiment offers consumers pre-programmed music channels, 21, artist favorite's lists, and on-demand access to 30, songs from a single song library. This convergence of broadcast music channels with a personal song library is a first in the music business. To develop this song library or database , PBM does not rely upon traditional radio programmers to find, select, classify, or rate individual songs or program its music channels.

Instead, a combination of highly automated computer systems, third party data sources, and trained PBM librarians is used. New digital technology has created challenges traditional programming techniques did not have to deal with.

First and foremost is the task of choosing music from an unfiltered universe of roughly 8,, songs that listeners can now access for free on their own. Fortunately, Broadcast Data Systems and others have demonstrated that only a tiny portion of this available universe has any relevance to consumers.

And, the iTunes top lists always look very similar to the corresponding Billboard Charts. In summary, this explosion in technology and access has not really changed what most people want to listen to very much. What it has done is created an enormous need to filter this song universe effectively. Most consumers do not have the time on their own to search an 8,, song universe for music that is relevant to them.

They need someone else to filter it and organize it into a library and pre-programmed playlists so it is easy to use. Many listeners now belong to massive social networks, whose members can obtain illegal copies of songs and share or distribute them to anyone they choose. This is too much work for most consumers who just want to listen to good music.

The vast majority of discovery still comes from music that is filtered, organized, and broadcast in some form. By way of illustration, there are now nearly , garage bands on MySpace.

Filtering is very useful to pre-load a library that includes only a tiny fraction of the song universe available. In the present embodiment, it is filtering 30, songs out of 8,, Traditional song selection techniques rely upon expert individuals searching through their best online and offline sources, listening to music and selecting what to include.

For terrestrial radio and satellite radio conglomerates, this is pretty simple. That is because they offer extremely narrow playlists aimed at highly specific demographic groups. Digital services, on the other hand, normally support hundreds of channels that collectively include from 10, to 18, songs on average.

They then fingerprint these recommended song collections by various characteristics music genome, etc so they can match them to consumer preferences. As described above, recommended songs are also assigned to various themed playlists as a second method for consumers to access the same collection. While BDS was the first to apply song-matching algorithms in the music industry, the present embodiment does not use this type of technology to construct libraries or music channels.

The present embodiment also does not use traditional programming staff. Instead, the present embodiment relies upon two highly automated proprietary systems. One deals with publicly available sources that primarily include songs from the major labels and a few dozen important indie labels. The second system called the PBM Remote Contributor Network, focuses on artists likely to sign a major label contract within three years. For publicly available material, the present embodiment identifies and tests over individual experts, charts, and playlists from leading periodicals, music websites, broadcasters, file sharing networks, and selected social network.

See FIG. These sources are constantly revised. These processes are preferably automated. In total, five stages of acquisition, filtering, and classification are used. These publicly available sources, including broadcasters of every variety, rely primarily upon a tiny catalog of featured artists that are heavily promoted by major record labels and a handful of indies.

To address this limitation, a Remote Contributor Network to be described below has been devised. This network comprises trained contributors located in the world's largest music markets, who filter and submit song candidates, preferably over the Internet. Instead, they are looking for artists likely to sign with a major label within 3 years.

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