Algorithms for mixing and mastering audio are having a growing impact in the global music industry as artificial intelligence innovators find applications in a variety of scenes. Throughout the music industry, the music writing process varies largely from artist to artist.
While some artists write their own songs, others hire professional songwriters to produce radio hits by following the music trends of the year. However, whether an artist writes their own songs or not, a crucial part of the song creation process is the mixing and mastering of tracks — a job reserved for professional music mixers that are often supervised by a music producer.
This process requires careful attention as the overall changes in this process can make or break a song. However, music mixers are finding that artificial intelligence technology can help streamline and perfect this process.
The Rise of AI
Artificial intelligence is a field of study in computer science that has been finding its way into a wide range of industries. AI has been found capable of innovating in industries where computer algorithms are able to simplify work that consists of analyzing and following data patterns.
Thus, the technology is completely transforming industries around the world, including healthcare, finance, education, management, transportation, analytics, and manufacturing and logistics. With the ability to process and disseminate data at faster-than-human speeds, this technology is able to facilitate a lot of the data-heavy dirty work that can take a person days, weeks, or even months to get through.
Although a relatively new technology, AI has experienced substantial growth since 2016, attracting the interest of major tech corporations including Google, Amazon, and other tech startups.
As AI continues to expand its ability to process data and handle logistical problems, people are able to dedicate more time to tasks that require a human touch, which has proven helpful for the sound engineering and production in the music industry.
However, because AI is still relatively new and serves mostly as computer science technology that completes basic human requests and tasks, companies still recognize the need for human troubleshooting. Without a person monitoring vital company information or files, businesses run the risk of experiencing extensive data mistakes that can occur due to small computer errors.
Transforming the Music Industry
Sound recording has progressed in waves since the invention of the phonograph in 1877, going from an acoustic era to an electrical era that included sound on film. It was then followed by the magnetic era before arriving at the present-day digital era in 1975.
Throughout each period of time, advancements in technology allowed people to develop new processes that increased the quality of sound recording and engineering for musicians. The advancements in music recording and mixing/mastering technology have dramatically changed the sound of music throughout the last few decades.
Today, artists are able to control and perfect the sound of each of their songs by using AI-based audio-mastering platforms like LANDR, which launched in 2014 and provides an inexpensive alternative to human-based mastering services.
The AI-based mastering service proved to be successful among artists, announcing that more than 2 million musicians used its music creation platform to master 10 million songs since the company launched. AI-based mixing and mastering algorithms are helping songwriters get through the initial balancing of music more efficiently, which gives them more time to spend with the minute details of sound development.
Machine learning can and has simplified some song-writing processes by digging deep into stores of music pattern data to select song chords, music tempos, and other standard composition aspects of songs.
It may even be capable of writing entire songs that compare to songs written by humans, but there’s no doubt that songs written by individuals will continue to have more success for the foreseeable future. In all creative processes, especially music composition and writing, artificial intelligence is unlikely to produce entire works of art on its own for a long time.
New Songwriting and Mastering Processes
Although it’s likely that AI-based audio mastering may be displacing some human mixing and mastering jobs, people who go through AI-based mastering platforms are likely musicians who would otherwise be mastering their music themselves.
For the most part, top artists are still using the best mixing and mastering professionals in the music industry to perfect their albums — such as mixing engineers like Jason Goldstein, who has worked with best-selling artists like Jennifer Lopez, Rihanna, Mary J. Blige, and Beyoncé Knowles.
Titled “I AM AI,” the album created a buzz in the music community by being marketed as the first album to be co-produced by AI. Using a variety of AI-based music platforms, the artist built songs using AI-generated music based off her instructions for BPM, rhythm, key, mood, and instrumentation, and constructed lyrics around the sonic mood of the song that was produced.
Although there was certainly decision-making on her part, the music was generated by various AI platforms. The rise of AI in the music industry has transformed and simplified many sound engineering processes that created a lot of additional work for musicians in the past.
Although the process of balancing the levels of individual tracks and blending the sound in a recording to create the best version of a song is best done by a professional sound engineer, AI-based mastering programs are helping smaller musicians achieve higher-quality mastering on their tracks.
The more advanced new technology becomes, the more it tends to spark ethical questions about how many human processes we will give up to technology. However, AI is helping give some artists without the means for humans-based mastering the opportunity to achieve their ideal overall sound, which is one of many ways AI is leveling the playing field in the music industry and helping drive the technological evolution of music.
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