Music is a universal language that brings people together from all over the world. As emerging technologies help us communicate better, artificial intelligence is beginning to overtake our hearts, minds, and even our ears.
Artificial intelligence is opening up a world where users can automate, personalize and learn. The music and education sectors are not immune to the efficiency of emerging technologies. Smart bots like Amper's AI program can now compose their own albums, while other smart apps, like SmartMusic, allow users to experience compositing and production. However, before emerging musicians can find the right resonance with their audiences, they need to develop their talents.
Artificial intelligence will be the next big learning tool. For now, AI can't completely replace the creative process, but it does make music education and composition easier than ever. But how will machine learning revolutionize music education and inspire continued human innovation in music?
For music students and emerging musicians, artificial intelligence in education technology (AIEd) can re-work music education to become more supportive and creative, while democratizing the medium and scope for musicians to create new songs.
Calculating sound and rhythm
In a traditional music classroom, teachers share their expertise and provide instruction on rhythmic patterns, rhythmic overlap, and chord progressions through interaction with and demonstration of physical instruments. But AIEd could be a useful hand for human teachers in the classroom.
One of the first smart classrooms in the United States was created by a music professor at Penn State University. In this artificial/virtual reality environment, known as the "first classroom," apprentice professors can practice with AI students. If educators can use AI to help music educators, they can also use the technology to help music students.
Companies like Third Space Learning are already implementing platforms that provide artificial intelligence software to monitor and improve teaching and learning. In this case, students interact with the tutor through an online whiteboard as they answer questions.
By analysing 100,000 hours of audio and written data, the company and scientists at University College London are identifying how artificial intelligence is helping to enhance students' knowledge and performance. In addition, success indicators can be collected from the raw audio data to show how many questions were asked, how useful the session was to the student, and what the instructor said about the session.
Other education companies, such as Pearson, say that existing computer systems can already provide one-on-one tutoring and facilitate group discussions. They can also simulate complex environments or situations for learning purposes. In their report, Smart Unleashed: the debate over AI in education, they predict that AI can provide feedback on a student's progress, state of knowledge, and even emotions in seconds. Companies can then create instruments and supplemental instructional programs that are connected to digital features and platforms that monitor, instruct and use data to analyze student activity and performance in the music classroom and at home.
In fact, says Lauristel, author of Pearson's artificial intelligence report, "lifelong learning partners" - robotic tools in the form of devices or apps - can ask questions, offer encouragement, provide advice, and connect to online resources. If students are struggling, such as with problematic rhythms, peers can help guide their performance or even suggest new techniques.
From Classroom to Recording Studio
In a way, everyone learns from real life experiences that they don't usually encounter in the classroom. But with the development of artificial intelligence, music education can continue to be prevalent in physical or virtual classrooms and in and out of recording studios with apps and tools.
Today, music learning echoes outside the classroom and into the music studio, and musicians are often incorporating AI tools into their own musical development. Douglas Acker and his research team at Google have implemented the "Magenta" project, a machine learning research project that helps them understand how computers create various forms of art and music. The neural learning project provides a synthesizer and a note sequence generation model that interacts with human musicians. Through Google, users can even use a plug-in for the leading digital audio workstation, Ableton. These tools for musicians, provided by the open source machine learning library Tensorflow, offer insights into the way musicians learn in educational and professional music facilities.
Several startups are helping these learning experiences with apps and tools that facilitate music creation. Popgun has the first artificial intelligence that learns from human musicians, skills that complement and enhance musical compositions, and the whim of its creators. Weav is another startup that creates songs for changes in tempo, beat, energy and mood based on the listener's whims. Lars Rasmussen, co-founder of Weav, says human artists continue to create its adaptive music. In the future, Rasmussen predicts that AI will help, rather than replace human artists altogether.
All the data musicians store in the cloud for these new technological devices can provide a valuable record of a music student's progress. Indeed, AI can help us analyze the melody, the beats per minute, and so on. But music education is largely intangible, even as there are many ways to interpret its style and character. Even Beethoven insisted that music is never perfect because of different interpretations, and that every performance cannot be copied exactly or even judged like any other.
To a large extent, AIEd is still in its infancy. While it can store data and automate simple tasks, it cannot answer broader, theoretical, or even cultural questions. Yes, AI will disrupt the music education system, but combined with real teaching and instruction, it can be a tool to provide more access and accuracy to the arts.
Music's most powerful tool: the ear or artificial intelligence?
Artificial intelligence has yet to mimic the human ear in its nuance and emotional depth. In fact, the AI is still learning how to program itself to teach and understand music. But the power of human creativity can be nurtured by new, mass-market technologies that can help everyone, even the most junior player, become a more experienced and perceptive musician. In the future, music teachers may give a standing ovation to a more personalized education as AI becomes a partner in lifelong learning.
Enrique Cadena Marin (DJ ECM) is one of the fastest growing EDM artists and producers in Latin America.
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