By Ivan Linn
In today’s contemporary digital landscape, the convergence of artificial intelligence with various industries is profoundly reshaping both our lifestyles and professional environments. Wavv has recently unveiled its plans to initiate a comprehensive series of investigations centered on the synergy between the music industry and the realm of artificial intelligence. We maintain a steadfast belief that the amalgamation of music and cutting-edge technology will spearhead the future’s innovative and progressive evolution within the music sector.
We are unwavering in our commitment to closely monitor the progress in this domain and deliver to you the most up-to-date information and insightful perspectives. We eagerly anticipate the forthcoming release of a series of pertinent research reports in the days ahead. We extend an open invitation to all our friends and colleagues who share our enthusiasm for this subject to actively participate in our research endeavors and embark on an exploration of the potential and future trends at the intersection of artificial intelligence and music. Let us collectively bear witness to and facilitate the harmonious amalgamation and advancement of the music industry and artificial intelligence, forging a brighter tomorrow together!
1. Music Industry Status Quo
1.1 Streaming Dominance: Streaming services, such as Spotify, Apple Music, and Amazon Music, were the primary means of music consumption. Streaming has surpassed physical sales and digital downloads in terms of revenue. The global recorded music market grew by 7.4% in 2020, and the growth was driven by streaming, especially by paid subscription streaming revenues, which increased by 18.5%. Total streaming (including both paid subscription and advertising-supported) grew 19.9% and reached $13.4 billion, or 62.1% of total global recorded music revenues.[¹] This means that streaming has become the main source of revenue for the music industry.
1.2 Independent Artists: The rise of digital platforms and social media empowered independent artists to reach a global audience without the need for major record labels. Many artists were choosing to remain independent or sign with smaller, more artist-friendly labels. Some independent singers, such as Chance the Rapper, have built up a singular reputation for remaining unsigned to any record label and for dropping their songs online for free.[²]
1.3 Diversification of Revenue Streams: Musicians were exploring various revenue streams beyond music sales, including merchandise, endorsements, brand partnerships, and Patreon-style fan support models. Music artists’ incomes are becoming increasingly diverse.
1.4 Diversity and Inclusion: The industry was facing increased scrutiny and calls for greater diversity and inclusion, both in terms of artists and behind-the-scenes professionals.
1.5 Technology and AI: Technology continued to shape the industry, using artificial intelligence for music production, recommendation algorithms, and data analytics to understand consumer preferences. The popularity of streaming services such as Spotify and Pandora shows that people like to be guided in their music choice and discover new tracks with the help of algorithms.[³] Generative AI has made its debut on Spotify’s stage already. And AI-Powered Recommendations at Spotify have maximized user engagement.[⁴] At the same time, streaming media platforms analyze audience preferences through big data to determine the investment direction of music production. In response to the trend of the times and platform innovation, a large number of singers try to use AI for creation. AI composition technology has been used in pop music, such as pop singers SKYGGE and Kiesza, who used AI to create some songs like Hello Shadow.[⁵]
1.6 Live Music Challenges: The COVID-19 pandemic had a profound impact on the live music industry. Concerts, festivals, and live events faced cancellations or restrictions. The industry was adapting to virtual concerts and hybrid events, but the recovery process was ongoing. In 2020, due to the pandemic-induced cancellations of live concerts and performances, physical revenues which declined 4.7%; and revenues from performance rights which declined 10.1%. However, at the same time, total streaming revenues grew 19.9%.[⁶]
2. Interest Chain of Music Distribution and Monetization
2.1 The Entire Process of Music Monetization
The traditional music industry encompasses several key stages, from the creation of original music content to its release and distribution. These stages include:
Within the music industry, artists are facing unfair compensation due to the traditional processes and middlemen involved. Major music streaming platforms open artists to a wide range of consumers and fans; however, due to the nature of how revenue is determined within these companies, the time and money it takes for artists to reach consumers ultimately trickle down to artists profiting anywhere around 10–16%.[⁷]
2.2 Music Revenues Distribution
- Recording studios. They get recording fees.
- Record companies. They take the lion’s share of record sales.
- Music publishers. They get publishing fees and a cut of sales. For non-recorded music, publishers take most of the sales.
- Sales platforms. Along with publishers, they take a share of sales.
- Music creators. They only get a fraction of record sales and royalties.
Though percentages vary by contract, record companies and publishers reap the vast majority while artists remain in the weaker position. According to industry research reports, music artists can earn only 12 percent of their income from their creations.[⁸]
3. Music and AI’s Intertwined Evolution
3.1 Music Composition: AI can generate original music compositions by analyzing existing songs and patterns in music. This can be a useful tool for composers, helping them overcome writer’s block or providing inspiration for new compositions. AI can generate music in various styles and genres. For example, the YouTube pop singer Taryn Southern used the AI system Amper Music to create multiple songs for her album I AM AI.[⁹] The copyright concerns surrounding AI-generated music compositions and audio tracks are currently a subject of both concern and controversy. Nevertheless, within the legal framework, a definitive and clear definition is conspicuously absent.
3.2 Music Analysis: AI algorithms can analyze music to extract information about its structure, key, tempo, and emotional content. This analysis can be useful for musicologists, DJs, and music streaming services for better categorization and recommendation.
3.3 Music Generation: AI-powered tools can generate music in real time based on user preferences. For example, apps like Wavv MusicGPT, Stability AI, IBM Watson Beat, Amper Music and Soundtrap can create customized background music for videos or podcasts.
3.4 MIDI Generation: AI can convert audio tracks into MIDI files, which can then be edited and rearranged by musicians and producers. This is valuable for remixing and sampling existing music. As it is widely recognized, unlike other modes of production, music sampling is notably intricate. This practice lacks established conventions or theoretical frameworks to guide creators, instead demanding a combination of patience, a discerning ear, and a unique skill set. However, the advent of AI dramatically alters the landscape. Employing AI for music sampling is theoretically viable and technologically feasible, it remains a subject of extensive discussion among industry experts. Yet, the transition from theory to practice has, as of yet, failed to yield any definitive success stories.
3.5 Auto-Tuning and Vocal Processing: AI can automatically correct pitch and timing issues in vocals. Auto-tuning software like Auto-Tune uses AI algorithms to achieve the desired vocal effect.
3.6 Music Recommendation: Music streaming services like Spotify use AI to recommend songs and playlists based on a user’s listening history and preferences.
3.7 Instrument Tuning and Sound Processing: AI can assist musicians and audio engineers in tuning instruments and processing audio signals. It can help in achieving specific sounds and effects in music production.
3.8 Collaborative Music Creation: AI can facilitate collaboration among musicians who are physically separated. It can generate musical accompaniments, which musicians can use as a basis for their performances.
3.9 Music Analysis for Licensing and Copyright: AI can be used to analyze large music databases to detect copyright violations and protect the intellectual property of musicians and composers.
3.10 Virtual Musicians and Bands: AI-powered virtual musicians like “Magenta” and virtual bands like “The Annoying Orange” can create music performances and collaborate with human musicians.
3.11 Music Education: AI-powered apps and platforms can help individuals learn to play musical instruments, compose music, or understand music theory through interactive lessons and feedback. Carnegie Mellon University’s music teaching AI Hanon can detect complex repertoire performances, pointing out missed notes, tempo changes, rhythm errors, etc. Compared to human teaching, it is more precise and comprehensive. In addition, there is an interactive and educational music service product Yousician, which can use audio analysis technology to detect students’ performances, give real-time feedback, and automatically generate practice pieces suitable for the student’s level. And there is Music Prodigy, an interactive teaching platform that can use AI to assess students’ abilities and design personalized courses. They all serve as AI virtual music teachers for humans.
3.12 AI-Generated Lyrics: Some AI models are capable to generate song lyrics, which can be used by songwriters for inspiration or to complete songs. Many of these software perform well in this regard.
3.13 Remastering and Restoration: AI can enhance the quality of old recordings by reducing noise, restoring lost details, and improving overall audio quality.
4. Epilogue
The rapid development of digital technology has brought an unprecedented huge impact to the music industry but also opened up the possibility of innovation. These changes have brought about tremendous changes in the way music is created, performed and spread, injecting new vitality and impetus into the entire music industry. Nowadays, with the continuous development of artificial intelligence technology, the combination of music and AI has become the focus of people’s attention. AI technology can provide strong support and help for music creation, music performance and music industry operations, thus bringing more rich and diverse music experience to music creators and listeners.
For music creators, AI technology can provide them with more efficient and accurate music creation tools and auxiliary means, helping them quickly get inspiration, create music works, and even recommend suitable musicians to cooperate through algorithms to expand the field of music creation. At the same time, AI technology can also revolutionize music interpretation. For example, the analysis and decoding of music through artificial intelligence algorithms can grasp musical emotions and expression techniques more accurately, to provide more musical performers with rich and diverse interpretation methods and expression techniques. In addition, AI technology can also bring new business models and operational ideas to the music industry operation. For example, the analysis of user behavior through AI algorithms can provide more accurate recommendations and personalized services for music platforms, and improve user experience and user engagement. At the same time, AI technology can also help music platforms realize intelligent management and operation, and improve operational efficiency and service quality.
To sum up, the combination of music and AI will usher in an unprecedented industry revolution, bringing more innovative possibilities and new experiences to music creators, performers and listeners, as well as injecting new vitality and impetus into the entire music industry. Let’s look forward to this as a bright future!
[1]: IFPI issues Global Music Report 2021
https://www.ifpi.org/ifpi-issues-annual-global-music-report-2021/
[2]: Why Chance the Rapper — who just made Grammy history — gives his music away for free.
[3]: How Do AI Music Recommendation Systems Work
https://cyanite.ai/2021/09/02/how-do-ai-music-recommendation-systems-work/
[4]: The Inner Workings of Spotify’s AI-Powered Music Recommendations: How Spotify Shapes Your Playlist
[5]: SKYGGE And Kiesza Collaboration “Hello Shadow” Was Composed By Artificial Intelligence.
[6]: IFPI issues Global Music Report 2021.
https://www.ifpi.org/ifpi-issues-annual-global-music-report-2021/.
[7]: Wavv Music, MOS Music NFT Gold Tier, 72h Flash Sale
[8]: Insider, Musicians Get Only 12 Percent of the Money the Music Industry Makes, https://www.rollingstone.com/pro/news/music-artists-make-12-percent-from-music-sales-706746/.
[⁹]: Taryn Southern on Being First to Use Artificial Intelligence to Make Album:‘Sky Is the Limit’
https://www.thewrap.com/taryn-southern-i-am-ai-album-artificial-intelligence/
