Tag Archives: music technology

The Frank Sinatra song that not even Frank Sinatra heard

Reading Time: 4 minutes

As Christmas is fast approaching, we are starting to hear the holiday classics everywhere. From All I Want for Christmas at the Supermarket to Rockin’ Around the Christmas Tree on the radio – Christmas songs are virtually unavoidable. 

But I’d like you to think of the artists behind these songs – most of Spotify’s Christmas Hits playlist[1] is comprised of songs recorded or written before the first manned mission to the Moon.

Naturally, many of the authors and performers listed in the credit sections of these songs are long gone – Bing Crosby died in 1977, Nat King Cole passed away in 1965 and Frank Sinatra departed in 1998. 

Frank Sinatra
source: http://enterate24.com/hace-104-anos-nacio-el-cantante-frank-sinatra/

It’s a shame that we won’t be able to hear any new songs from them.

But what if it doesn’t have to be that way?

That’s where OpenAI’s Jukebox comes into play.

Debuted in April 2020, the technology analysed over a million songs[2], along with their lyrics and metadata (release date, genre, mood) and is now capable of generating full tracks in the style of any well-known artist. The company shared a range of demos, designed to resemble artists such as Alan Jackson, Katy Perry, or Elvis Presley. Most notably though, the song that stands out is “Hot Tub Christmas”, in the style of Frank Sinatra. While the “recording” quality might not be perfect, the timbre of the “singer’s” voice is eerily similar to that of the legendary American singer.

Though the lyrics have been co-written by a language model and OpenAI researchers, the chord progressions and instrumental cohesion are very well replicated in the computer-generated mp3s. The team behind Jukebox is aware of the software’s faults, as “[…] the generated songs show local musical coherence, follow traditional chord patterns and can even feature impressive solos, we do not hear familiar larger musical structures such as choruses that repeat.”2

Jukebox doesn’t analyze the actual notes in the songs, but only relations between pitch over time. An upside of such an approach is the possibility of highly realistic human voice creation. For their future endeavors, OpenAI plans to integrate a note-to-MIDI technology which would detect the rhythms and exact notes, which would allow for a deeper, more natural, and precise song creation – perhaps with the use of software instruments or synthesizers for higher file and sound quality.

Jukebox, at this point, is treated by the music industry as a mere curiosity, with no real applications – even despite a new feature of creating an acapella file from user-generated lyrics being introduced. This dynamic might change in a relatively short time if Jukebox becomes able to create classically written songs, providing the notes, rhythms MIDI files behind them. With such possibilities, songwriters and producers could streamline their music creation processes and massively increase their output. 

The current market situation is visualized by the fact that most of the investments poured into creative AI come from Venture Capital and Tech Corporations – not from the Music Industry.[3]

At this point, it does not seem like any songwriter or producer jobs are endangered. High quality audio files have incredibly many timesteps which encode data – a standard 4-minute-long song in a .wav 44.1 kHz file will contain over 10 million timesteps.[4] Currently, a song needs to be almost fully produced and designed by a professional before being rendered into such a complicated audio file.

The process of AI art generation is slowly being integrated into commercial culture, with the generator Midjourney winning the Colorado State Fair Fine Arts Competition.[5] Jukebox and similar technologies are often criticized for taking away the humanity out of art, while some perceive it as an opportunity to augment their creations through technology.[6]

“Théâtre D’opéra Spatial” – the AI-generated, contest winning piece of art
source: https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html

To me, it seems inevitable that Artificial Intelligence will be widely used in the music industry – major labels will push for anything that can give them a competitive edge in business. 

We must also take into consideration the legal implications of Jukebox.[7] Our laws don’t include AI “artists” and thus, there might be copyright implications. Who is the de facto author of such a song? The AI developer, or the person who entered prompts into the technology to create a specific tune? How do we split royalties for such songs? Furthermore, is it acceptable ethically to expand dead artists’ catalogues?

In conclusion: AI is slowly entering into creative arts, especially the music industry, thus expanding songwriters’ and producers’ output and possibilities. It appears that in this case, the risk of actual people being replaced by technology is lower than in easily automated and routine operations. 

This time, I’ll ask the classic question: do you think that AI art is proper art? Should it be publicly disclosed that a song or a painting was generated through Artificial Intelligence?

Let me know what you think in the comments!

Until next time,


[1] https://open.spotify.com/playlist/37i9dQZF1DX0Yxoavh5qJV?si=d4fa601b2c3f4418

[2] https://www.cnet.com/science/these-ai-generated-katy-perry-and-elvis-songs-sound-hauntingly-real/

[3] https://blog.songtrust.com/current-state-of-ai-what-songwriters-need-to-know

[4] https://openai.com/blog/jukebox/

[5] https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html

[6] https://fortune.com/2018/10/25/artificial-intelligence-music/

[7] https://themix.musixmatch.com/post/ai-in-songwriting-4-practical-applications

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Inhuman music

Reading Time: 3 minutes

In the 21st century, artificial intelligence can do everything. Painting pictures, driving cars, helping doctors in medicine, and what about music? Does AI know how to compose music and write lyrics for songs?

In truth, an artificial intelligence can do this, too. Not with a soul, not with such a huge meaning, as a human does, because a robot has no feelings, but still knows how and even writes lyrics for music.

How exactly do neural networks create music? The general principle is that the neural network “looks” at a huge number of examples and learns to generate something similar. But it is impossible to formulate a task for a neural network to write beautiful music, because it is impossible to create a formula that will fulfill this task, since this is a non-mathematical requirement. It is interesting only when the neural network reproduces something that exists. The approach by which this music is created is called an auto-encoder (Generative Adversarial Network). It works like this:
We compress the music at the input into a very compact representation and then expand it back to its original form. A compact representation does not allow you to remember everything completely that was in the music. Therefore, the neural network is forced to put some common properties for music into the software part. And then, when generating music, we take a random sequence of numbers, apply the rules about the knowledge of music learned by the neural network and get a piece of music that looks like a human.

Turing Music Test
How to understand that a piece of music created by a machine is really worthy of our attention? To test the work of artificial intelligence systems, a Turing test was invented. His idea is that a person interacts with a computer program and with another person. We ask questions to the program and the person and try to determine who we are talking to. The test is considered passed by the program if we cannot distinguish the program from a person. For example, the DeepBach algorithm was tested, which generates notes in the Bach style. More than 1.2 thousand were interviewed. People (both experts and ordinary people) who had to distinguish the real Bach from the artificial one. And it turned out that it was very difficult to do this — people can hardly distinguish between music composed by Bach and created by DeepBach.

What about the lyrics?
Well, we’ve sorted out the musical compositions, but what about the lyrics for the songs? Can artificial intelligence compose poetry? Yes, and this task is even easier than writing melodies, although there are also enough difficulties here — the algorithm needs not only to “come up” with a meaningful text, but also to take into account its rhythmic structure.
In 2016, the developers of Yandex released the album “Neural Defense”. It includes 13 songs, the lyrics for which were composed by artificial intelligence. A year later, the album “Neurona” was released with four songs in the style of Nirvana, the verses for which were also generated by neural networks.

Thus, we see that artificial intelligence is able to write even music and lyrics for it, but will it ever replace songs written by a person in which feelings and life situations were invested?






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Mischievous AI judges your taste in music

Reading Time: 3 minutes

Do you want to know how terrible your taste in music is to end an already terrible year? Look no further than the “How Bad Is Your Spotify” project on Pudding.cool, that will ridicule your taste in music, in a good way of course.

If you’re a Spotify user you probably got your Spotify Wrapped earlier this month which nicely summed up your music taste for this year. The Pudding’s new AI tool is nothing like that. Besides analyzing your listening history, it interacts with the user in a playful manner.

The app uses artificial intelligence which was trained by by Matt Daniels and Mike Lacher for The Pudding.

Once users visit the website they are asked to grant access to their Spotify to let the “sophisticated A.I” judge their “bad taste in music”.

The bot explains that it has “been trained on a corpus of over two million indicators of objectively good music, including Pitchfork reviews, record store recommendations, and subreddits you’ve never heard of,” when you click on “how do you know what’s good?”

The quiz takes users through a series of amusing questions making you feel like you’re chatting with a passive-aggressive snarky friend. It said things such as: “lol… omg… okay hold up… Do you really listen to [artist name]…?”

After the A.I is done mocking your musical taste with its questions, it analyses your answers and tells you how “bad” your Spotify is.

The AI bot gives a rundown of tracks the users listen to “too much,” artists they listen to “to an uncomfortable extent,” rates how “basic” your musical taste is and highlights the decade you’re “stuck” in.

Mike Lacher, one of the brains behind the witty bot says,”We wanted to make something similar to Spotify Wrapped, but instead of celebrating your music, it would insult it. For us personally, we knew that the stuff we stream privately is often embarrassing, so we thought it would be funny to make a bot that would look through all that stuff and judge you. We wanted it to feel like a judgemental friend, or a snobby record store clerk.”

Many, after using the app, went on social media to share their results. One twitter user commented “the accuracy of the how bad is your Spotify thing is terrifying.” Another user said “I tried the “how bad is your Spotify playlist” AI and I am too embarrassed to share the results…”

It’s all fun and games but it’s important to realize that artificial intelligence and the music industry are incredibly linked together.  The fact that they can store an incredible amount of information for comparison and analyze human taste on a platform like Spotify can open a new era for the music industry.

Go check out “How bad is your Spotify?” on pudding.cool !




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Spotify’s Tastebuds tool will enhance your social music discovery

Reading Time: 3 minutesThe new function aimed at Spotify will allow us to slightly broaden our musical tastes. All thanks to our friends from the platform.

New Spotify’s feature logo
Source: https://techcrunch.com/2019/12/18/spotify-tastebuds/


How music sharing options look like now?

Thinking about what Spotify can offer today, we can mention social media integration. It is a popular feature that enables users to connect their Spotify accounts to their Facebook and Twitter profiles. That lets them access their friends’ favorite music and playlists and share their choices with others as well. Individuals can create, share, and edit playlists with other listeners. If users want recommendations, they can integrate their system with Last.fm, an application that provides music recommendations based on listening history. However, this is an external application that does not belong to Spotify. You can also view a Friend Activity ticker of songs your Facebook friends are currently listening to on the desktop app. You can search for specific users and follow them or view playlists they’ve made public too. Spotify doesn’t promote user search much anyway.


Why Spotify need a change?

Sharing playlists on Spotify is not a problem, but when it comes to speeding up the entire algorithm, things get complicated quickly. If we listen to music in a random way, it is known that Spotify will not start sending us recommendations based on it. If that were the case, playlists created using algorithms would not suit certain user’s tastes. Social sharing has never been the main priority for Spotify. The Activity Feed, which shows what your friends are currently listening to, is limited to the desktop version of Spotify. The in-app messenger for sharing music was nixed in favor of letting users share songs on social media or on their Instagram Stories. Apparently, that was a mistake as far as we know that Tastebuds is coming.

Tastebuds feature on Spotify
Source: https://techcrunch.com/2019/12/18/spotify-tastebuds/


But what will Tastebuds really give us?

As the information on the site is telling: Tastebuds will let your friends discover music that you trust. This description appears in the tab that has not yet been launched, but the developers have already sewn it in the application – in the left column, next to the Home Page, Browse and Radio. The prototype feature was discovered in the web version of Spotify by reverse engineering sorceress Jane Manchun Wong. She gave some more details on how it works. By tapping on the pen icon, users can view information about what their friends have been playing most. Then, they can easily listen along or add songs to their own library.

Tastebuds feature discovered in the web version of Spotify thanks to reverse engineering
Source: https://techcrunch.com/2019/12/18/spotify-tastebuds/

Spotify Tastebuds code
Source: https://techcrunch.com/2019/12/18/spotify-tastebuds/


It remains to wait for deployment

When will the new feature come into effect? There is no official information about it. A Spotify spokesperson confirms that they are always testing new products and experiences, but have no further news to share with the audience. For now, anyone can access a non-functioning landing page for the feature at https://open.spotify.com/tastebuds. Tastebuds could be a rebranded version of the Friends Weekly playlist that was discovered in May 2019. Whatever it may be, the test could be a sign of more social listening features to come.

Social is a huge but under-tapped opportunity for Spotify. Social recommendations could get users listening to Spotify for longer. While competitors like Apple Music or YouTube might offer similar music catalogs, users won’t stray from Spotify if they become addicted to social discovery through Tastebuds.

Do you think Tastebuds is just what Spotify needs? Maybe something else would make the application more user-friendly? Share your opinion.



[1] https://www.crunchbase.com/organization/spotify#section-overview

[2] https://rms.pl/aktualnosci/sprzet/3239-spotify-tastebuds

[3] https://www.spidersweb.pl/2019/12/spotify-tasetbuds-czego-sluchaja-znajomi.html

[4] https://www.theverge.com/2019/12/18/21028474/spotify-tastebuds-playlist-friends-music-discovery-social-sharing-feature

[5] https://techcrunch.com/2019/12/18/spotify-tastebuds/

[6] https://www.engadget.com/2019/12/19/spotify-social-music-discovery-tastebuds/

[7] https://www.theverge.com/2018/5/9/17337182/spotify-testing-new-friends-weekly-playlist

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