What’s the biggest challenge in making virtual strings sound as expressive as a live performance?
In general, and I think this applies to other instruments beyond strings (take a synth melody for example), the biggest challenge is to capture the nuances of human expression. Talking about strings specifically, a human can have slight pitch fluctuations, bow pressure variations, dynamic movement and all kinds of organic imperfections.
In my opinion, these “perfect” imperfections and dynamic performances are what create emotional depth in a strings section. If you think from a purely automation standpoint, imagine assigning an automation lane for all these parameters to, let’s say a MIDI violin, and would capture a human playing it, there would be hundreds of slight variations in the automation.
With a sample library, it’s important to replicate that by paying close attention to detail and automating dynamics, articulations, velocity layers, and expression. If we don’t focus on these, it’s easy for a string section to sound robotic and emotionless.
It reminds me of how AI-produced music often feels, lacking the emotion that real human composers bring. In my opinion, all the imperfections are what give music its soul, something I think AI still struggles to replicate in a convincing way. I think mainly because music is something genuine – something real. We capture a moment and transmit a feeling, and that’s what we need to translate in order to make not only our strings more expressive, but our music as well. If we don’t add these nuances in virtual strings, the result can feel a bit emotionally disconnected, like an AI generated composition, if you know what I mean.
Of course, no virtual library perfectly replicates the nuances of a live orchestra, but with the right techniques, we can get pretty close.
Pro tip from Paradoks: When automating string dynamics, imagine how a bow moves naturally: longer phrases need smoother mod wheel curves, while shorter notes benefit from sharper moves.
