Posts
 |
| Photo: Vallabh Rao |
 |
| Photo: Aiva team |
Pierre Barreau is a computer scientist, who also happens to be a registered music composer. Pierre, after watching the science fiction movie Her, in which an AI composes a piece of music, was inspired to build an AI that can compose music. “That really struck a chord with me because I originally come from a family of artistes. At the same time, I studied Computer Science at university and I always had a passion for both domains,” says Pierre. “So this is how I thought AI-generated music was something I had to get involved in one way or another and I teamed up with people close to me with similar interests.”
The team consists of computer scientists Pierre and Denis Shtefan who work as the CEO and CTO of the startup respectively, Vincent Barreau as the COO and Arnaud Decker as the CMO. All the team members are music composers. The startup has received seed funding from an incubator in Luxembourg and will be closing another round of investment soon.
Launched in February 2016, Aiva wrote ‘her’ first composition for Piano Solo, inspiring her creator to push the boundaries of what AI-made music can sound like. On French Bastille Day 2016 (July 14), Aiva wrote her most emotional and melancholic piece to date. The piece is set to be the finale for the album Genesis.
“Even amongst her kind, she is quite special; as opposed to the AI systems that we use in our daily lives — search engines, voice-over assistants, auto-pilots — Aiva is able to write beautiful and emotional music, a deed that is considered to be deeply human,” says Pierre, on his artificial music composer.
Using Deep Learning, Aiva learns by reading many compositions (15,000 pieces written by Mozart, Bach, Beethoven etc.), to extract musical features and build up an intuition of music theory. During training, Aiva creates a mathematical model that represents its own definition of music, and then uses that model to compose completely original themes. The music can be customised by inputting different types of datasets that have been gathered over the months. “For example, if we want to create an epic music, we can train Aiva on epic / cinematic music. We are also working on conditional input generation, i.e., specifying other types of data like text, images to generate a fitting music to that data,” adds Pierre.
Read more...
Source: YourStory.com
