![]() Impressed to see the quality of autogenerated vocals has gone way up! Sounds real but in a foreign language. ![]() In 2020, Jay-Z’s record label filed copyright strikes against a YouTube channel, Vocal Synthesis, for using AI to create Jay-Z covers of songs like Billy Joel’s “We Didn’t Start the Fire.” After initially removing the videos, YouTube reinstated them, finding the takedown requests were “incomplete.” But deepfaked music still stands on murky legal ground. ![]() They already have, albeit around simpler AI systems. “We strongly emphasize the need for more future work in tackling these risks associated to music generation.”Īssuming MusicLM or a system like it is one day made available, it seems inevitable that major legal issues will come to the fore - even if the systems are positioned as tools to assist artists rather than replace them. “We acknowledge the risk of potential misappropriation of creative content associated to the use case,” the co-authors of the paper wrote. During an experiment, they found that about 1% of the music the system generated was directly replicated from the songs on which it trained - a threshold apparently high enough to discourage them from releasing MusicLM in its current state. Still, the Google researchers note the many ethical challenges posed by a system like MusicLM, including a tendency to incorporate copyrighted material from training data into the generated songs. Induces the experience of being lost in space." /XPv0PEQbUh The model generates 24 kHz music from rich captions like "A fusion of reggaeton and electronic dance music, with a spacey, otherworldly sound. ![]() Yesterday, Google published a paper on a new AI model called MusicLM. Most of the “lyrics” range from barely English to pure gibberish, sung by synthesized voices that sound like amalgamations of several artists. And while MusicLM can technically generate vocals, including choral harmonies, they leave a lot to be desired. Some of the samples have a distorted quality to them, an unavoidable side effect of the training process. motivational music for workouts).īut MusicLM isn’t flawless - far from it, truthfully. Even the experience level of the AI “musician” can be set, and the system can create music inspired by places, epochs or requirements (e.g. ![]() That’s not all. MusicLM can also be instructed via a combination of picture and caption, or generate audio that’s “played” by a specific type of instrument in a certain genre. See below, which came from the sequence “electronic song played in a videogame,” “meditation song played next to a river,” “fire,” “fireworks.” “time to meditate,” “time to wake up,” “time to run,” “time to give 100%”) and create a sort of melodic “story” or narrative ranging up to several minutes in length - perfectly fit for a movie soundtrack. Moreover, MusicLM can take several descriptions written in sequence (e.g. The Google researchers show that the system can build on existing melodies, whether hummed, sung, whistled or played on an instrument. MusicLM’s artificial intelligence capabilities extend beyond generating short clips of songs. Here’s another sample, generated from a description starting with the sentence “The main soundtrack of an arcade game.” Plausible, right? The caption for the sample below, for example, included the bit “induces the experience of being lost in space,” and it definitely delivers on that front (at least to my ears): ![]()
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