Listen Local

Demo Slovak Music Database

Thu, 17 Dec 2020 17:10:00 +0200

We are finalizing our first local recommendation system, Listen Local Slovakia, and the accompanying Demo Slovak Music Database. Our aim is

Show how the Slovak repertoire is seen by media and streaming platforms
What are the possibilities to give greater visibility to the Slovak repertoire in radio and streaming platforms
What are the specific problems why certain artists and music is almost invisible.

In the next year, we would like to create a modern, comprehensive national music database that serves music promotion in radio, streaming, live music within Slovakia and abroad.

To train our locally relevant, alternative recommendation system, we filled the Demo Slovak Music Database from two sources. In the opt-in process we asked artists to participate in Listen Local, and we selected those artists who opted in from Slovakia, or whose language is Slovak. In the write-in process we collected publicly available data from other artists that our musicology team considered to be Slovak, mainly on the basis of their language use, residence, and other public biographical information. The following artists form the basis of our experiment. (If you want to be excluded from the write-in list, write to us, or you want to be included, please, fill out this form.)

Click here to view the table on a separate page

Modern recommendation systems usually rely on data provided by artists or their representatives, data on who and how is listening to their music, and what music is listened to by the audience of the artists, and certain musicological features of the music. Usually they collect data from various data sources, but these data sources are mainly English language sources.

The problem with these recommendation systems is that they do not help music discovery, and make starting new acts very difficult. Recommendation systems tend to help already established artists, and artists whose work is well described in the English language.

Our alternative recommendation system is a utility-based system that gives a user-defined priority to artists released in Slovakia, or artists identified as Slovak, or both. The system can be extended for lyrics language priorities, too. Currently, our app is demonstration to provide a more comprehensive database-driven tool that can support various music discovery, recommendation or music export tools. Our Feasibility Study to build such tools and our Demo App is currently under consultation with Slovak stakeholders.

Listen Local is developing transparent algorithms and open source solutions to find new audiences for independent music. We want to correct the injustice and inherent bias of market leading big data algorithms. If you want your music and audience to be analysed in Listen Local, fill this form in. We will include you in our demo application for local music recommendations and our analysis to be revealed in December.

Tiny Rooms: A Label That Connects DIY Scenes

Mon, 14 Dec 2020 08:10:00 +0200

www.tinyroom.nl

An interview with Utrecht recording artist, performer, composer, and producer Stefan Breuer, manager of Tiny Room Records.

For fans browsing the city after a given show, what do artists in Utrecht recommend as far as things to see, do, listen to, or other advice for visitors?

For anyone checking out one of my shows in Utrecht, I definitely recommend a walk around the city if they have some down time. Nearby our space, one can stop at De Klub for a bite to eat, the local brewery De Kromme Haring for a beer, or the record store / coffee bar Koffie Leute around the corner. For those with more time during the day, I also recommend a few local record stores like Dig It or Plato or maybe a walk around Utrecht centre. For the full Utrecht experience, I recommend a dive into the postrock, slowcore, indiefolk vibes of this friendly city with bands if you can catch bands like The Fire Harvest, I am Oak, Homemade Empire, or This Leo Sunrise, among others. And of course there’s the Nijntje Museum, the Dom tower, and the canals.

Where do your artists hope to play next year? Where do they hope to find new fans?

Personally, I’d like to play in any city with a vibrant DIY scene. In the Netherlands, I’d like to rebook all the shows in Haarlem, Amsterdam, Eindhoven and in Liège (BE) that were cancelled due to COVID. I’d also like to add some shows in Groningen, Nijmegen, Enschede, Maastricht and Arnhem because I know they also have some small DIY scenes there, too.

Stefan Breuer / Tiny Rooms.

I’d like to play in any city with a vivid DIY scene. In the Netherlands, I’d like to re-book our shows that were all cancelled in Haarlem, Amsterdam, Eindhoven, and Liège. I’d like to add some shows in Groningen, Nijmegen, Enschede, Maastricht and Arnhem because I know they have small DIY scenes there too.

How do you and your artists see the role of YouTube, Spotify, Facebook, algorithms, big data?

We try to make sure all our bands are present on all of these platforms and actively engage with content as much as possible, but there’s not really enough time to get the most out of YouTube, for example, when you are also trying to write and record music, book shows, not to mention that artists involved with my label all have other work and families to be with. I’d say we all know the potential of the internet and big data, but the best we can do right now is just let as much happen with that as we can. We don’t really feel like we have any control over what happens in that area or our overall “success” on social media.

How much is your label really focused on Utrecht specifically? Where would you say the true home base of your label is, whether geographically or spiritually? Where do you have the strongest audience?

So Tiny Room Records is actually based in Utrecht and Bilthoven. Utrecht is a city. That’s where the scene happens and that’s what we’re part of. I live in Bilthoven, which is 5 kilometers away from Utrecht. It’s next to the woods. It’s quiet. It’s small. It’s perfect for focusing on creating beautiful music and art. There’s inspiration from the sight and smell of nature and not a lot of distractions like pubs and venues. So as a musician, my home base is Bilthoven. Running a label, it’s Utrecht because all the shows, recordings, and rehearsals happen there. It’s also where we’ve held most of the Tiny Room nights, and our 5th year anniversary festival.

How important is touring for your label’s roster? How do artists select touring locations? Where do you think your label’s strongest potential for finding a new audience would be?

Our rehearsal space and venue Studio Patrick generates a DIY scene which is unique for Utrecht but not necessarily Europe. In the NL, we’ve always had a strong connection with Subblicious in Leiden, Lepel Concerts in Groningen, Roodkapje in Rotterdam, Vondelbunker in Amsterdam, Katzwijm Studio in Voorhout, De Ruimte in Amsterdam, the art scene around Danielle Papenborg in Nijmegen, and the Van Onderen festival. We’re also connected to labels like Subroutine, Moving Furniture, Snowstar, Coaster, Narrowminded, Geertruida and so on.

We use these contacts to set up tours and other possibilities long the way. Sometimes it doesn’t work out wen you have a Canadian artist playing for two people in Heerhugowaard, but you don’t know until you try. That’s how I stumbled upon the scene around Honest House, a label and booking agency in Liège, Belgium a couple years ago. It turned out to be perfect for all our bands and we still maintain a good partnership with them in order to regularly produce a few nights of live music. We will start working with them again around live music, of course, when we are post-COVID. Same goes for Lousy Moon Records in Köln. I think there are a lot more places like this and it would be great to have more insight about where the super DIY/indie/arty/folk/postpunk/kraut/experimental songwriting stuff is happening. I know it’s there in a lot of cities in its own form, but the audience is so small that it’s hard to get to know all the cool places. I’d like to focus on NL, Belgium, Germany, and France since these areas are the most doable for a weekend or week long tour.

What’s more important? Belonging to a scene, a genre, a subculture, or a location? How are these connected?

For me, it’s important to belong to a scene. These are the people here in Utrecht that care about what we do, our shows, and our releases. They come to support the bands, have a great time, and we all know each other, have the same values, and we’re good friends, too. Maybe some call that a “subculture” too, but no one I know calls it by a particular name.

You need a location to get together, but you can build a scene anywhere, I guess. My dad even built a vibrant music scene in the middle of nowhere in France in a village of 200 people. About genre, I don’t want to focus on one thing. For the label, I have a specific thing in mind — music that I really love — which is based on my own taste. Most people at the shows we host are most interested in music that’s more experimental, unique, even a bit raw and unusual. I can be ambient, indie rock, punk, sloppy folk, doom songwriters, slowcore, noise, etc. If it’s too catchy or a “normal” radio friendly singer/songwriter, the audience scratches their heads and I won’t have a good time either.

What kind of insight and intelligence would you like from Listen Local, which tries to crunch a lot of data about location, language, and the genre of small acts?

I would like to know where similar scenes are in other cities, where they host shows, and who books them, mainly in the Netherlands and surrounding countries, but also possibly in Italy, Switzerland. The bonus is that this also gives me some cool new bands to listen to as well. They would probably have a good audience here in Utrecht and we could probably do a “gig swap.”

Ideally it would make booking easier so that you won’t have to reinvent the wheel each time and hunt for new places, although that can also lead to some great adventures and memories, so I would not rule that out entirely. About genres, I hope to find bands that look beyond genre and experiment with sound, culture, and performance.

Demo Recommendation App

Tue, 01 Dec 2020 00:00:00 +0000

A machine learning recommendation system is always following a strict goal, and it keeps getting better and better in achieving that goal. The most fundamental question is who is setting the goal? A media platform that wants to maximize the time you spend in front of the screen, regularly watching ads. A digital streaming provider that wants you to always listen to their music. Or yourself? Our demo recommendation system allows you to set the target. You can start from a radio hitlist, a radio playlist, or your own playlist, and design your own target, very similarly to how regulators set their local content requirements. Do you want to have 20% Slovak language recommendations? Or 15% performed by artists and bands who identify as Slovak? Or Dutch? Or 20% songs made in Slovakia by Slovaks?

In this demonstration, we modified Spotify’s algorithm, because we believe that it is the best proprietary system in the world with the most open API. While Spotify does not reveal its algorithm or its’ precise goal setting, it gives back a lot of information about the music it can potentially recommend. It also has a relatively well documented system, so we know roughly what is going on behind the scenes. This is not true for most DSP systems.

Spotify is recommending a playlist of songs or recordings, and we do the same, but we allow you to control the target of the system and we reveal the steps. Similarly, to Spotify’s or YouTube’s system, we first create many candidates to the playlist, then we narrow it down to songs that we believe fit best your original playlist.

Our demo recommendation system is a utility-based system because it starts from Spotify’s original, native recommendations, but places a higher value to songs that follow your target settings.

The highest level of utility is given to Spotify’s generic recommendations, if they match the target criteria, i.e., they contain enough music from artists with Slovak identity, or Slovak releases, or Slovak language songs. We believe that Spotify’s algorithm is great if it works under control.
The second highest level of utility is given to artists whose works fulfil the criteria, and according to Spotify, they are like the artists’ in the reference playlist. Spotify’s similarity is based on both musicological and descriptive features and user interaction with the music. When they perceive an artist to be similar, he or she is likely to be similar.
The third highest level of utility is given to songs that are coming from the same genre as (some of the) user’s playlist items, but which are ‘Slovak’. We create a set of song candidates, and then we compare them to the original songs in the user’s playlist. Using a similarity measure, we eventually create a playlist that fulfils the target criteria set by the user.

Our recommendation flow

Most recommendation systems use three type of information: information about the music itself, information about the users who played or interrupted the music, and whatever textual information the provider finds in the data the artists/labels sent in, or journalist or the band wrote about themselves. In our demonstration, we want to show that if you want a system to work for you, you must be able to control the data inputs – for example, the words that describe your music in a way that is understandable for Spotify’s, YouTube’s, or our system. We demonstrate this with the Demo Slovak Music Database, which is an open access, opt-in, opt-out database. The artists and Slovak musicologists have a say in how the information about the data is treated.

We also want to demonstrate that for the promotion of a labels, a creator collective’s, or a country’s repertoire, it is very important to cleverly set goals. From an ethnomusicological point of view, it is not sufficient to say that you would like to have 20% Slovak music. In our demonstration we are creating a gradual definition of ‘Slovakness’.

There are many targets that can set to promoting “Slovak music”, or “Slovak jazz”, or “European music”, or “new music”. We can train algorithms that tell you which is the city or country where people listen to most similar music to “Slovak pop”. We can build an app that gradually introduces classical and contemporary Slovak or European music to pupils in a school, starting with music that they are already familiar with and appreciate, and step-by-step recommending relevant new discoveries, always allowing them to give feedback. Or we can help radio editors to fill up a part of their airtime with artists who live in their city, region, or country.

Algorithms can have many unintended consequences. For example, they can recommend music that they already know better in a small country, eventually reducing the already small audience reach and market opportunity of local artist. We believe that this can only be prevented if local artists and their managers understand what a streaming providers’ or media platform’s algorithm does – what data goes in and what sort of recommendation comes out.

Our approach is open collaboration – we use data that is open for the participants, and algorithms that can be studied or even modified by our partners. This way not only bad consequences can be prevented, but the most desired outcome can be achieved by artists, creators, or their representatives. We believe that you can only achieve your goals if you understand and control both the data and the algorithm.

Demo Slovak Music Database

Tue, 01 Dec 2020 00:00:00 +0000

Modern recommendation systems as well as the use and monitoring of local content guidelines ("radio quotas"") require reference data about recorded music that will be played or recommended to be played, and metadata, or data about the data. Slovakia currently does not have a database that could help the monitoring of radio quotas, or which could help the LaLa music export, or a Slovak label to find audience for its songs.

Our Demo Slovak Music Database shows how to fill this need. It is used in our Listen Slovak Demo App, and we show in our Feasibility Study what procedures and data is needed to create and constantly update a Comprehensive Slovak Music Database for these purposes.

The demo database contains information about Slovak artists, composers, and their sound recordings released in Slovakia and abroad. It can form the basis of radio quota monitoring, new type of recommendations, educations applications, or just simply improving the likelihood that Spotify or YouTube will recommend a particular Slovak sound recording or video.

The entire database can be accessed as SQLite database, or in the form of .csv, .xlsx or .rds tables. Please contact for help if you want to try it out our use it – it is free, open access, and we are happy to assist any interested reader to try it out. We also placed on this website a summary of the table, so that you can review which artists are featured in the database.

This will be seen in the front page, and the project description phase the rest. Therefore, add this this text:

We added an easy to browse and download simplified version of the Demo Slovak Music Database to the website [here] – artists and their representatives can review how we see them or ask to be added or removed. You can read [there] a bit more about the database and its use, and you can use the [Contact] options to get access and help to data database in several formats that can be used with free of charge, open source software.

Artists

Opt-in Process

The opt-in process was based on a voluntary questionnaire that SOZA and Reprex sent to various Slovak artists and labels. We asked age, performance maturity, language use and location specific questions about the artists. The opt-in procedure is still open – we are happy to include more artists into the demo database and demo application, and we hope that we can continue this project with the Slovak Arts Council and other partners to make the database truly comprehensive, i.e. to contain all Slovak music unless the artist wants to be featured as Slovak. Want to be deleted? The opt-out process is very simple in the demo phase: contact us and let us know that you do not want to be part of the Demo Slovak Music Database.

Write-in Process

The write-in process was necessarily subjective, because we could not, and did not want to use GPDR protected personal information. The current broadcasting quota defines Slovak artists by residence, which is a personal data that we do not have, and which is not applicable for deceased Slovak artists. As an alternative, we created a long list of candidates to the database based on listening habits in Slovakia. We considered artists who appeared on radio charts, or who appeared on various, Slovakia-specific playlists on Spotify, or who described their music with the Slovak adjective, like Slovak rock or Slovak hip hop. We read-in all the biographies of the English language Wikipedia in the Slovak female and Slovak male music performer categories. We narrowed down this long-list with the help of a Slovak native-speaker musicologist, Dominika Semaňáková, to identify artists who should be considered Slovak. The criteria of inclusion were publicly available city affiliation (where the artist or group works), birthplace, place of death, language of lyrics when applicable, language of the song or work titles, and publicly available information about the artist.

In the demo version we tried to limit the data written-in, and we only concentrated to Spotify (explained here why.) The following features are attached to each artist’s Spotify ID: [don’t translate labels, these are identifiers in the database files if somebody downloads them.]

spotify_popularity: A number between 0 and 100 describing the artist’s popularity based on stream counts on the Spotify platform.
spotify_followers: An artist’s total number of subscribers on the Spotify platform.
spotify_genre: Up to three genres associated with each artist.
total_reccomendations: The number of recommendations associated with each artist after three iterations of our algorithm. Artists with zero recommendations are practically invisible for Spotify, and likely never recommended. One of our main goals is to avoid this cold start problem, which affects about 15% of Slovak artists in 2020. [don’t translate cold start]
spotify_genres: Up to three genres associated with each artist.
any_slovak_release: A value of 1 is assigned if the artist has released some work in Slovakia, 0 otherwise.
slovak_release_pct: The percentage of sound recordings released in Slovakia.
any_slovak_title: A value of 1 is assigned if the artist has some work with a title in Slovakian, 0 otherwise.
all_slovak_title: A value of 1 is assigned if all the artist’s work is in the Slovak language, 0 otherwise.
all_english_title: A value of 1 is assigned if all the artist’s work is in Slovak language, 0 otherwise.
known_slovak_city: Slovakian cities associated with the artist.
considered_czech: A value of 1 is assigned if the artist is also considered to be Czech. Our greatest challenge is to define the boundaries of Slovakness and being “Czech”.
popular_song_titles: A short selection of the artist’s most popular songs.
latest_popular_releases: The date of the artist’s most recent popular releases.
spotify_url: The artist’s or bands’ official Spotify URL.
official_website_url: The artist’s or band’s official website.

Sound Recordings

The Demo Slovak Music Database contains up to ten sound recordings associated with 0 Slovakian artists, comprising a total of 3937 unique tracks. When the Spotify API is queried for top track recommendations, 19 artists do not yield any results. For each other artist, the following features are included: [Footnote 2: A full list of the data Spotify keeps for each track can be consulted at https://developer.spotify.com/documentation/web-api/reference/tracks/get-audio-features/]:

danceability: An approximation to how suitable a track is for dancing, considering musical elements such as tempo, rhythm stability, beat strength, and overall regularity. A value of 0.0 is least danceable and 1.0 is most danceable.
energy: A perceptual measure of intensity and activity aggregating features including dynamic range, perceived loudness, timbre, onset rate, and general entropy.
key: An approximate overall key for the track. Spotify expresses this in pitch notation, and here this is converted to the notation’s tonal counterparts.
loudness: Average loudness of a track in decibels (dB).
mode: An approximation to a major-minor modality: 0 is minor, 1 is major.
speechiness: Detects the presence of spoken words in a track on a scale between 0 and 1.0.
acousticness: A confidence measure from 0.0 to 1.0 of whether the track is acoustic. Values above 0.5 are intended to represent instrumental tracks, but confidence is higher as the value approaches 1.0.
liveness: A confidence measure from 0.0 to 1.0 of whether the track is live depending on the detection of an audience in the recording.
valence: An approximate measure from 0.0 to 1.0 describing the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g. happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).
tempo: The overall estimated tempo of a track in beats per minute (BPM).
duration (ms): Track length in milli-seconds.
time_signature: An overall approximation to the track’s beats per measure.

Genres

We all know that genres are very important for music discovery and music selection, but music cannot be very well described with natural language words. Any taxonomy of genres is dependent on the language, for example, jazz may mean a bit different for music fans in Slovakia, Japan, and the United States. Digital streaming services and media platforms usually use AI applications that understand English language taxonomies. Therefore, it is critically important to have a correct understanding and use of the Slovak and English versions of genre descriptions. A song that is accidentally labelled as rock instead of pop may become invisible, because it does not fit the rock audience’s taste. It will be skipped by many listeners, and the AI algorithm will learn that this is not a good song. Even though pop audiences may like it.

Our databases genre table map abstract distances of Slovak genres, such as Slovak indie or Slovak jazz to Belgian indie or Japanese jazz. This is a very important part of our database, and it requires a broader consensus among radio editors, music export promoters, labels, artist, and computational musicologists to get this right. However, or [opt-in process] show that the lack of knowledge about the way genres work in global platforms is an important reason of low visibility for Slovak music.

Listen Local: The Youniverse from East to Southwest

Mon, 30 Nov 2020 08:10:00 +0200

Guitarist Jerguš Oravec and singer Tammy Nižňanska

The Youniverse as a band and creator collective was formed in 2015 around guitarist Jerguš Oravec and singer Tammy Nižňanska. Changing genres and forms, creating musical and visual worlds spiced up with BDSM attire they have been playing shows in Slovakia and releasing a full-length album in 2018. Tammy is a bilingual Slovak, who is more comfortable in the English language due to her upbringing than in the country’s language, and against what she feels to be the expectation of the local audience, she sings in English. No wonder that she is also looking for ways to expand their universe beyond the country borders.

Tammy believes that The Youniverse it at a crossroads. To be more successful at home, they would have to switch to their native Slovak language, and to be more successful in English they would have to connect better to foreign audiences. She believes that the local audiences often seek a different quality than what she offers – the purity of her voice instead of auto-tune, or the native language instead of the language of rock and roll. Therefore, their main targets are the Southwestern part of the United States, particularly Los Angeles in California and Austin in Texas, and they believe that their eccentric show would probably create interest in Japan, too.

What do they know or think of big data algorithms? The Youniverse hired a Google Analytics manager and they try to figure out how they could reach out to fans in far away places, or to understand how their songs occasionally find their ways to people in different countries. Tammy knows that Spotify employs playlist curators who are helped with computer-based algorithms to find new music, but she is not familiar with the process – that is why she volunteered to participate in our Listen Local project and our Feasibility Study for the creation of a Slovakian music promotion service.

Listen Local: Katarzia

Wed, 25 Nov 2020 15:10:00 +0200

Katarzia. Photography by Ladislav Kyllar

Katarzia, or Katarína Kubošiová, is a Slovak singer, lyricist and producer. In 2020 she released her fourth album Celibát with the main themes of loneliness and self-appreciation. Album was created in collaboration with the producer Jonatán Pastirčák.

Katarzia started her career as a folk singer. In the past years she moved on towards electronic music. She describes her current sound can as a mix of folk and electropop. The tour to promote her newest album Celibát had been planned for spring 2020, unfortunately due to the Covid-19 pandemic had to be postponed indefinitely. As many other artists, Katarzia thinks that the current situation is not easy.

At the moment, I am not working on any new projects. I am looking for a new job. Once the pandemic is over, I would like to stay where I am now, and return to the clubs to play for my audience. As I sing in Slovak, I know where my place is – I don’t want to perform abroad, of course, unless I turn to techno music. On a more personal level, I would like to live in New York – not as a musician, tough.

Katarzia is originally from Nitra, Slovakia and she has been living in Prague for a couple of years.

I live in Dejvice – there is a nice clubroom there, but I don’t visit that much. I enjoy going to National Theatre, Dejvice Theatre, Meetfactory, Archa Theatre and Rudolfinum. All the old classics.

Despite the restrictions during the pandemic, Katarzia managed to shoot a video for her song Hoří i voda from Celibát.

The music video is a short film, directed by Jay Walker, an American who lives and works in Prague. Girls in film –- an organization that supports women in the film industry –- participated in the production of the video. The song is about women rights and equality.

Previous albums:

Generácia Y (2013)
Agnostika (2016)
Antigona (2018).

Listen Local: Why We Need Alternative Recommendation Systems

Mon, 23 Nov 2020 17:10:00 +0200

The first version of our demo application

Recommendation systems utilize knowledge about music content and their audiences while also pursuing the objectives or needs of recommenders.

The simplest recommendation systems just follow the charts: for example, they select from well-known current or perennial greatest hits. Such a system may work well for an amateur DJ in a home party or a small local radio that just wants to make sure that the music in its programme will be liked by many people. They reinforce existing trends and make already popular songs and their creators even more popular.

If the recommendation engine is supported by big data and a machine learning system – or increasingly, a combination of several machine learning algorithms – the general modus operandi is to exploit information about both content and users in order to achieve certain goals.

How algorithmic recommendation systems work?

How recommendation systems work?

Spotify’s recommendation system is a mix of content- and collaborative filtering that exploits information about users’ past behaviour (e.g. liked, skipped, and re-listened songs), the behaviour of similar users, as well as data collected from the users' social media and other online activities, or from blogs. Deezer uses a similar system that is boosted by the acquisition of Last.fm – big data created from user comments are used to understand the mood of the songs, for example.

Spotify makes 16 billion music recommendations each month in 2020.

YouTube, which plays an even larger role in music discovery, uses a system comprised of two neural networks: one for candidate generation and one for ranking. The candidate generation deep neural network provides works on the basis of collaborative filtering, while the ranking system is based on content-based filtering and a form of utility ranking that takes into consideration the user’s languages, for example.

What makes these systems common is that they maximize the algorithm creators' corporate key performance indicators. Spotify wants to be ‘your playlist to life’ and increase the amount of music played during work or sports in the background, during travelling, or active music listening –- i.e. maximizing the number of hours spent using it, and do not let empty timeslots for other music providers, such as radio stations. YouTube and Netflix have similar targets. They are in many ways like commercial radio targets, which want to maximize the time spent listening to the broadcast stream. Radios and YouTube, in particular, have similar goals because they are mainly financed through advertising. For Spotify or Netflix, their key financial motivation is to avoid users' cancelling their subscriptions or changing it to different providers, such as Amzon, Apple or Deezer.

What is the problem with black box recommendation systems?

What they also have in common is that they do not aim to give a fair chance to each uploaded song, serve equally every artist, or provide whatever equality of chances for English, Slovak or Farsi language content.

They tend to reinforce trends similarly to music charts, but with far bigger efficiency. As the Dutch comedian, author and journalist Arjen Lubach explains the YouTube algorithm, to keep their personal recommendations engaging all the day and all of the night, they create a comfortable universe for the user allows little distraction in. If the user wants to listen to global hit music, or stoner rock, it will never be distracted with anything else.

Zondag met Lubach on Dutch public broadcaster VPRO. Click settings sign to change the language of the captions.

The problem with such hyper-personalized media is that they leave no room for public activities. Public broadcasters, which had a monopoly to television broadcasting in most European countries until the early 1990s, for example, were aiming to air a diversity of news, knowledge and access to local culture. Many countries on all continents have maintained local content guidelines for broadcasting on public, commercial and community television and radio channels, for example, local music and films, and reliable news as a public service. Personalized media-, social media- and streaming platforms do not have such obligations.

Black box recommendation systems usually maximize a corporate key performance indicator, and they are not subject to usual public new service or local content regulations that traditional broadcast media is.
The goal and the steps that the algorithm is pursuing is not know to content creators, and they do not know when will the algorithm work for their benefit or against them.

Transparent and regulated AI

In our view, utility-based recommendation system can provide a bridge between current, corporate-owned systems that maximize a media or streaming platforms' business indicators.

Public new service requirements or local content requirements (“national quotas”) set for commercial broadcasting are similar to utility or knowledge-based recommendation systems. A utility-based recommendation system, for example, would prefer from two candidates for a playlist the one that has a Slovak composer, or a performer from Wales, or which has Farsi lyrics.

Our Demo App creates recommendations on the basis of a pre-existing radio or personal streaming playlist that, by choice, contains a pre-defined ratio of music produced in Slovakia, or performed by Slovak artists. We will soon add Dutch and Hungarian choices to this demo, but naturally, we could add any city’s, regions', province’s our countries preferences into the app.

Our Demo App and accompanying Feasibility Study in Slovakia shows how can a regulator create better broadcasting regulations, learning from the experience with AI-driven streaming platforms, and how can it apply the goals of local content requirements (such as a certain visibility for Slovak or a city-based music) and public service requirements (for example, spreading reliable information or stopping hateful music.)

Access for all

We do not believe that the current heated discussion on the re-regulation of AI and music streaming will solve all the problems of independent artists, bands from ethnic or racial minorities, or otherwise vulnerable producers. New regulation can limit the unintended collateral damage of big data algorithms deployed by big corporations, but they will not bring down the benefits of AI to these creators.

Take the example of the controversial new initiative that let’s artists, labels and publishers to promote their music in exchange for a cut in royalty rates. While felt by many artists injust and even corrupt, it is an answer to the growing need to influence how the recommendation algorithms are promoting certain music at the expense of tens of millions of sound recordings that are not recommended.

We believe that algorithms create value for the users, and if artists are not happy to pay for corporations to influence black box algoritms, thatn they must collaborate and share data, and build large enough data pools so that they can deploy white, transparent algorithms that work for them.

Our Feasibility Study shows why it is important that creators have a control over what data describes their music, their biographies and other information online, because corporate streaming platforms use this information for their algorithms.
We should that with relatively little effort creators can pool enough information to create alternative recommendation systems that follow a more agreeable goal, that is sensitive to local content requirements and more access to new artists, women or black performers, or which suppress hateful lyrics.
The benefit of an open algorithm and pooled data is that artists can actively look for audiences in various age groups or in cities that are accessible for them on a performing tour after the pandemic.

Overall, we want to show that regulating black box, private algorithms and data monopolies is only a first step to damage control. Deploying white, transparent algorithms and building collaborative or open data pools can only guarantee fairness in the digital platforms, in recommendations, and generally in the use of AI.

Central & Eastern European Music Industry Report 2020

Wed, 29 Jan 2020 16:00:00 +0100

The predecessor of Reprex’s Demo Music Observatory, CEEMID together with the independent music distributor Consolidated Independent presented and discussed with stakeholders the Central & Eastern European Music Industry Report 2020 as a case-study on national and comparative evidence-based policymaking in the cultural and creative sector on the CCS Ecosystems: FLIPPING THE ODDS Conference – a two-day high-level stakeholder event jointly organized by Geothe-Institute and the DG Education and Culture of the European Commission with the Creative FLIP project.

The CEE Report builds on the results of the first Hungarian, Slovak, Croatian and Czech music industry reports are compared with Armenian, Austrian, Bulgarian, Lithuanian, Serbian and Slovenian data and findings.

Our research findings were earlier presented and discussed in Vienna, Prague, Budapest and Bratislava with stakeholders.

You can find the earlier presentations in the blog section of the website.

Executive Summary

The first Central European Music Industry Report is the result of a co-operation that started among stakeholders in three EU countries five years ago to measure the economic value added of music – the basis of a modern royalty pricing system. This gave birth to CEEMID, originally the Central & Eastern European Music Industry Databases, a data integration programme that now in 2020, covers all of Europe. CEEMID fulfils similar roles to the planned European Music Observatory and supports all pillars of the future pan-European system.

The comparison of Western and Eastern music audiences reveals key demographic differences that make the unchanged adoption of business practices from mature markets in the region questionable. Chapter 2 of this report will show these differences and their consequences on music markets, in terms of visiting and acquisition likelihood, frequency, seasonality and purchasing capacity. This is an example of how CEEMID fulfils the role of Pillar 3 (music, society and citizenship) in the planned European Music Observatory.

Chapter 3 contrasts market demand with the supply strategies of musicians. CEEMID has been surveying music professionals, including artists, technicians and managers about their working conditions, market conditions and plans for five years across a growing number of countries. In 2019 we invited 100 national and regional stakeholders to distribute our surveys. In some countries, our surveys already have several years of historic data, making the resulting musician database probably the largest ever source of data about how music is produced and how musicians live. We are constantly looking for partners to roll out this survey to new countries in new languages.

The CEE region has comparative advantages in big music events like festivals, and it has become one of the most important hubs for cultural tourism in the world. We explain this phenomenon in Chapter 4 by showing the differences in demand composition, demography and supply of venues in the second chapter. The lack of a modern and dense network of permanent music venues gave rise to magnificent music festivals in the CEE. Open’er, Sziget and Exit are among the biggest and best festivals in the world, closely followed by several smaller festivals in all countries. The share of festivals in the live music market is many times higher than in Western Europe and they provide vital export revenues to the local music economies. However, they play a limited role in finding new audiences for local artists, as they are increasingly programming for Western audiences by providing shows of international hits. They can only very partially fill in the gaps left by the small venue problem that hit the emerging markets harder than the UK or Australia, where policy action had been already taken to reverse the decline of the availability of smaller live music venues.

On the recording side, our analysis shows that modern digital services are growing at a faster rate than in mature markets. Because of lower repertoire competition, streaming quantities are similar for a typical Austrian, Czech, Hungarian, Polish or Slovak track than in the mature markets. However, revenue growth is limited because of the interplay of several analysed factors. Our analysis of the live and recorded music markets shows that CEEMID fulfils the roles of the Pillar 1 (music economy) of the planned European Music Observatory.

Most recorded music sales revenue in the region comes from streaming platforms, just like in the mature markets. Successful sales strategies require a solid knowledge of the global marketplace and the ability to understand and train sales algorithms. Micro-enterprises, such as independent labels, have very limited ability to cope with these functions, given that they do not have market research or R&D functions. CEEMID and Consolidated Independent have started initiating open, national R&D consortia to create the necessary concentration in data assets, analytical capacity and budgets to close this gap. As a first step, CEEMID and Consolidated Independent have created a large, independent music dataset based on hundreds of millions of royalty statement entries to create our market indexes, styled after stock market and bond market indexes. Streaming opportunities are fast changing as roll-out of streaming services is happening at a different rate in various territories; subscription charges and the exchange rate to the producer’s currency vary and repertoire competition emerges in the market. Our volume and revenue indexes in Chapter 5.3 are aimed at creating sales algorithms that optimize sales volumes and expected revenues. We believe that this analysis also reveals that CEEMID partially fulfils the roles of Pillar 2 (music diversity and circulation) and feeds important data into Pillar 4 (innovation).

The region has far bigger untapped potential than most music business executives believe. Households in the region spend a significantly lower share of their recreational budget on music than their Western, Southern or Nordic peers. The region has a lot of untapped cultural purchasing power because servicing is particularly challenging in both the live and recorded sides of the business.

This upside potential cannot be tapped without better pricing. Royalty levels are often very low in the region. Due to many combined effects analysed in this short report, the gap between royalties earned in the CEE and Western Europe is several times bigger than the difference in GDP or national average wage. These gaps are partly caused by special interests preventing collective management from charging appropriate tariffs for restaurants, media companies or electronic appliance importers and manufacturers, and partly by unfavourable taxation of cultural products and services.

CEEMID was designed to create economic evidence on royalty pricing, private copying compensation and the creation of economic value added in the industry. In the first Hungarian Music Industry Report of ProArt and in the first Slovak Music Industry Report we have shown that economic and taxation policies of the CEE countries aimed to support car and electronics manufacturing create a distorted, unfavourable economic regime for creative industries. We want to help local stakeholders with economic evidence to correct these discriminatory policies during the overhaul of the EU VAT system. We have been helping various national organizations with economic evidence, presented in the light of latest EU jurisprudence, to improve their pricing activities. Our thousands of indicators were also used in ex ante evaluations of granting schemes.

In 2020, all EU member states will change their copyright administration legislation because of the national implementations of the 2019/790 Digital Single Market directive. CEEMID provides evidence in several countries about the size and impact mechanism of the value transfer, and generally the widespread use of the copyright exemption for private copying. We believe that the thousands of pan-European music industry indicators that we have aggregated over the five years will play a vital role in these regulatory processes.

CEEMID fulfils its roles with a very thorough exploitation of the EU’s 17-years-old Open Data regime with the re-use of public sector information, and a very careful mapping of the music industry. These maps help us conduct annual surveys among musicians and the audience, and they help us connect (always with pre-approval and with a user mandate) to industry databases. We do not only cover the EU countries, but increasingly (potential) candidate countries and neighbourhood countries.

In our vision, this data collection and integration, i.e. Pillars 1-3 should be available for all music stakeholders, should remain public and publicly funded. The last Pillar of the observatory, innovation, is where private entities should compete. The founders of CEEMID and Consolidated Independent believe that this report demonstrates the business and policy benefits of such a system with the analysis of the Central & Eastern European music markets. We believe that this way CEEMID is in a position to serve most of the planned functions of the envisioned European Music Observatory, and we are looking for ways to make either our thousands of indicators, or our data collection and integration software open source and available for all stakeholders in the EU and its neighbours. CEEMID was born out of necessity to level out the different levels of public research and statistical coverage of the EU member states. In our view, private entities in the future should focus their investments in Pillar 4 of the planned observatory, i.e. competing in innovation with creating new models, algorithms and services based on data that is available throughout the European Union without giving further advantage to the already mature markets.

Building Practical Tools To Plan Better Tours, Record Promotion and Grants. Evidence from 10 countries

Mon, 11 Nov 2019 10:16:00 +0100

I am going to look back on the needs assessment of Hungarian music professionals in 2015 and Czechs in 2019.I will also compare the problems of the Hungarian scene in 2015, 2019 with the current issues in Czechia, Slovakia and Austria.

I would like to provide an opportunity on BUSH to give personal feedback to the artists and professionals who gave their personal details in our annual CEEMID Music Professional Survey from Hungary, or anywhere else in the region if they make it to BUSH. More details will be sent to your e-mail addresses, provided you have given us one.

Private Copying in Croatia

Thu, 31 Oct 2019 12:00:00 +0100

Press release: Studija: Naknade za privatno kopiranje (BTL) u Hrvatskoj drastično ispod prosjeka EU

Short summary in Croatian: Privatno kopiranje u Hrvatskoj Full text in English: Private Copying in Croatia

Comperative Study On The Music Markets of the CEE Region

Fri, 11 Oct 2019 10:16:00 +0200

I am going to present the Czech results from our regional Central European Music Industry Report, and the first version of a comprehensive, national music development program that we started to work on in the organization of SoundCzech with 25 music professionals representing more than 20 stakeholders in the How We Would Like To Work in the Czech Music Industry in 2020 ex ante evaluation workshop.

I would like to provide an opportunity on Nouvelle Prague to give personal feedback to the artists and professionals who gave their personal details in our annual CEEMID Music Professional Survey from Czechia, or anywhere else in the region if they make it to Nouvelle Prague. More details will be sent to your e-mail addresses, provided you have given us one.

Panel Discussion of the Central Euroepan Music Industry Report 2019

Fri, 20 Sep 2019 10:16:00 +0200

The panel discussion of the first comprehensive Central and Eastern European report (Albania, Armenia, Austria, Bulgaria, Croatia, Czechia, Estonia, Lithuania, Poland, Romania, Slovakia, Slovenia) will be in held on the Waves Music Showcase Festival and Conference.

The presentation 10Mb self-contained HTML file, takes some time to load

You can read a related blogpost here

Quoted from the conference agenda:

CEEMID – Central & Eastern European Music Databases was created out of necessity: many Central and Eastern European countries are lacking effective cross-industry or governmental statistics on music or on cultural industries in general. The lack of data makes the work of tour planning, record promotion, grant evaluation or royalty tariff setting very difficult in those countries where the need would be even greater for such activities than in the most advanced markets.

Musicians are the most known source of information

Daniel Antal developed a survey distributed among music professionals asking them about their experience. These surveys were designed to fill the gaps in the data collection of official statistics and other music and film industry sources. The first survey was made in 2014 in Hungary, and in 2019 it already included 11 countries. They had been filled out in the past years by more than 5000 creative industry professional, in 2019 in Austria, too.

Daniel Antal believes that the music business in most of Europe, including Austria, has many common, similar challenges and would need a lot more regional cooperation to solve them. With the CEEMID-report, presented at the Waves Vienna Conference. Daniel Antal gives a fact-based comparison and will suggest some possible policy and strategic solutions to be debated after.

Presentation of the Slovak Music Industry Report 2019

Tue, 26 Mar 2019 13:00:00 +0100

The venue is V klub, Národné Osvetové Centrum.

Slovak Music Industry Report

Tue, 26 Mar 2019 00:00:00 +0100

The whole report can be downloaded for free from the homepage of SOZA.

Press reports in Slovak:

SME: [SOZA predstavila prvú Správu o slovenskom hudobnom priemysle](Čítajte viac: https://domov.sme.sk/c/22084685/soza-predstavila-historicky-prvu-spravu-o-slovenskom-hudobnom-priemysle.html)

Kreatívna Europa: Historicky prvá Správa o slovenskom hudobnom priemysle prináša okrem analýz aj odporúčania pre budúcnosť

In Hungarian: Új Szó: Tudományosan a hazai zeneiparról

Slides

Spáva o hudobnom priemysle na Slovensku from Dániel Antal

Slides

Tue, 05 Feb 2019 00:00:00 +0000

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Documentation

Hungarian Music Industry Report

Fri, 01 May 2015 00:00:00 +0200

A ProArt zeneipari jelentése from Dániel Antal