[LAD] Rendering Softsynth Instruments To Sample Based Instruments - Automation

Hello everyone, This is my first post on this list, so please excuse me if I'm not following list etiquette. I don't think I can be called a developer, although I can get things done with Python scripts. I'm much more of an end user, a musician using linux live - LinuxSampler being my 'bread and butter' tool. I have a specific application in mind, and I dont think there's anything out there that does it: I want to 'sample' a softsynth (e.g. Yoshimi) / modelled software instrument. In other words, I want something that automates the following process: 1. Sequencially play 88 X N notes, where N is the number of velocity layers 2. Play them through a particular preset on the softsynth/modelled instrument (basically just send MIDI output to the softsynth/modelled piano, through ALSA/JACK) 3. Record each sound (corresponding to each note/velocity) as a .wav file (at a specified sample rate, etc) The sample files can then be converted into a .gig instrument sample using Gigedit. The advantage of this process would be that one can now use (more or less) the same sounds with MUCH less CPU usage. the disadvantage, of course, is the loss of tweakability, but I can live with that, especially in live contexts. I searched for an application that does this, and the closest I got to was this feature in Renoise: http://tutorials.renoise.com/wiki/Render_or_Freeze_Plugin_Instruments_to_Sa… But I don't use Renoise live. Which brings me to my question(s): 1. Am I right about there not being any application that does this? (I hope I'm not!) 2. If yes, can someone point me in the direction of how I might get about writing a script that does this? 2a. What Python modules would be useful? I just came across PyAudio and PySndObj, and checking them out. I'm sure there are *quite* a few people who would find such a script very useful, and I intend to make it available ASAP. My programming skills are limited, though, so any help in this regard would be appreciated. Thanks for your time and consideration! Cheers, Guru