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| author | Bent Bisballe Nyeng <deva@aasimon.org> | 2020-02-02 20:36:06 +0100 |
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| committer | Bent Bisballe Nyeng <deva@aasimon.org> | 2020-02-02 20:36:06 +0100 |
| commit | 3ef15a3cc62d7f4c361d04d15c5b97be030f7581 (patch) | |
| tree | 41d214b046c39c7877f05082fc1c3475733450fb /sampling_alg_lac2020 | |
| parent | 6be6f40b0eb5ce03aea60e2015e308457f78636e (diff) | |
Add motivation comment and make ascii figures tiny.
Diffstat (limited to 'sampling_alg_lac2020')
| -rw-r--r-- | sampling_alg_lac2020/LAC-20.tex | 10 |
1 files changed, 6 insertions, 4 deletions
diff --git a/sampling_alg_lac2020/LAC-20.tex b/sampling_alg_lac2020/LAC-20.tex index 9757e7a..7ee146d 100644 --- a/sampling_alg_lac2020/LAC-20.tex +++ b/sampling_alg_lac2020/LAC-20.tex @@ -274,6 +274,8 @@ \todoandre{Mention drawbacks.} \todoandre{Introduce high-level ideas of our work.} \todoandre{Make difference between humanization and sample selection clear.} +\todo{Motivation: Make sure we have the following covered: Randomized samples, + Prevent repetitions, Sample coverage (use all samples in the set).} \subsection{Related Work} \todo{I don't really know what to write, except about round robin. Is there any other common method or any academic literature? Are there other methods in open source programs?} @@ -290,12 +292,12 @@ The early versions of drumgizmo used a sample selection algorithm based on grouping of samples, each with a corresponding velocity range, with a number of audio files, each with a probability of being played in the group: -\begin{verbatim} +{\tiny\begin{verbatim} ________________ _________________ / \ / uniformly random \ -- input note --> | group selector | -- group --> | sample selector | -- sample --> [0; 1] \________________/ \__________________/ -\end{verbatim} +\end{verbatim}} \todobent{Write this algorithm in psudocode syntax.} @@ -305,13 +307,13 @@ Later a new algorithm was created using a normal distributed random number for the sample selection with the mean controlled by the input velocity and the stddev calculated on the number of samples in the instrument as well as their power span. -\begin{verbatim} +{\tiny\begin{verbatim} stddev \ ________ _________________ / \ / nearest power \ -- input note --> | random | -- power --> | sample selector | -- sample --> [0; 1] \________/ \_________________/ -\end{verbatim} +\end{verbatim}} In order to make this new algorithm the power of each note must be specified in the instrument data. |