But it is likely shrinking opportunities for newer apprentices. In most cases, people using the services would not be hiring someone to audio master their tracks anyway. “It’s never looking into the future to see how to create the next cool thing.”īirtchnell said that AI-based audio mastering is probably displacing some human jobs, but it’s hard to know how many. “They’ve basically said their engine keeps learning by looking toward songs that get uploaded into it - but that means it’s always looking toward the past,” he said. He said that while the algorithm is technologically impressive, it fell short because it lacked a taste algorithm in the part of the software dedicated to creative learning. Ryan Petersen, a Nashville-based producer and songwriter, played around with LANDR a few years ago and ultimately abandoned the service to return to human colleagues. “Maybe this is some indication of AI in creative practice, and I really think it is, but I think it’s a long way from creative work - even though there can be creative aspects,” said Dannenberg. But some aspects of mastering - like equalizing the loudness levels of different songs on a CD or trying to match the spectral content in bass and high frequencies - are a lot simpler to automate than composing a piece of music or doing music production. “In the space of music creation, I think that mastering is one of the more cut-and-dried practices that can be formalized relatively easily.” Mastering is still creative, and humans can hear things that programs can’t. “That’s a really big number.”ĭannenberg said that it makes sense for some artists to turn to algorithms for mastering. LANDR, which was launched in 2014, recently announced that more than 2 million musicians have used its music creation platform to master 10 million songs.Ī few years ago, Carnegie Mellon computer scientist Roger Dannenberg heard that online systems had mastered 1 million songs - and was shocked. It’s quixotically different from volume, he pointed out, “containing more presence and energy.” They also add loudness, which is the idea of making the sound fuller. “It’s quality control,” explained Birtchnell. A person can hear flaws in the music, such as issues in the spectral range or the stereo balance, and remove glitches, pops and crackles. The traditional way of audio mastering generally requires a room with specialized acoustics. He decided to investigate AI’s uses and trends of algorithm-based audio mastering in a new paper released in November. Many younger and newer artists use LANDR to master tracks they are releasing to launch their careers (they offer a monthly service that costs $9 for four tracks). “While it’s not always clear what mastering does, the music comes back and it sounds better.” Birtchnell, a musician himself, was intrigued when he heard about AI-based mastering services like LANDR that offer inexpensive alternatives to human-based mastering. “Mastering is a bit of a black art,” explained Thomas Birtchnell, a researcher at the University of Wollongong in Australia. Now, artificial intelligence algorithms are starting to work their way into this undertaking. One of those ineffable qualities is audio mastering, a process that smooths out the song and optimizes the listening experience on any device. (Inside Science) - When a song plays on the radio, there are invisible forces at work that go beyond the creative scope of the writing, performing and producing of the song.
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