Roadmap » History » Version 5
Version 4 (Jeremy Gow, 2012-10-30 02:23 PM) → Version 5/34 (Jeremy Gow, 2012-11-01 04:20 PM)
h1. Roadmap
The immediate goal is to have a stable release version that is compatible with sbcl 1.1
* To fix: ground-truth-segmenter class missing during compilation
* To fix: non-terminating method calls in amuse interface.
* Minor fixes for boundary cases thrown up by Turkish Makam data.
* Ensure
h2. Short-term
A simple configuration Configuration script: remove the need to edit paths in source code.
set local paths.
Debugged/consistent code on repository, then split release version from development branch.
Some basic benchmarks to ensure stability of future development versions:
* Use Conklin examples etc. versions.
Viewpoint selection:
* Adding viewpoint weights to output.
* Optionally specify: start point for search, min-links
* More flexible way for user to specify constraints on viewpoint search:
** Define labelled viewpoint classes
** Pairs/triples of labels/wildcards specify acceptable combinations
** User provides whitelist or blacklist spec
New basic viewpoints:
* cents - a higher resolution representation of pitch.
* comma
* metrical contour
Efficiency:
* Check/extend caching of models etc.
* Use sampling to estimate mean IC during VP selection.
h2. Mid-term
Viewpoint selection:
* Optimise based on match with existing IC values.
Allow user to specify structure of model.
* Determine order in which distributions are combined.
* Specify weights for particular combinations, e.g. weighted viewpoints, or weighted memory stores.
* Multiple memory stores.
* Specify alternative context strategies.
* Provide some prepackaged models, e.g. the current model structure.
Adding viewpoint weights to output.
New basic viewpoints:
* cents - a higher resolution representation of pitch.
* comma - this needs implementing?
More flexible way for user to specify constraints on viewpoint search.
h2. Mid-term
* Allow models to use predictive information (PI), expected PI and PI rate (as analogs to IC, entropy and entropy rate respectively).
* Feature selection/generation.
h2. Long-term
* Hierarchical structure. structure?
* Parallel implementation. implementations?
The immediate goal is to have a stable release version that is compatible with sbcl 1.1
* To fix: ground-truth-segmenter class missing during compilation
* To fix: non-terminating method calls in amuse interface.
* Minor fixes for boundary cases thrown up by Turkish Makam data.
* Ensure
h2. Short-term
A simple configuration Configuration script: remove the need to edit paths in source code.
set local paths.
Debugged/consistent code on repository, then split release version from development branch.
Some basic benchmarks to ensure stability of future development versions:
* Use Conklin examples etc. versions.
Viewpoint selection:
* Adding viewpoint weights to output.
* Optionally specify: start point for search, min-links
* More flexible way for user to specify constraints on viewpoint search:
** Define labelled viewpoint classes
** Pairs/triples of labels/wildcards specify acceptable combinations
** User provides whitelist or blacklist spec
New basic viewpoints:
* cents - a higher resolution representation of pitch.
* comma
* metrical contour
Efficiency:
* Check/extend caching of models etc.
* Use sampling to estimate mean IC during VP selection.
h2. Mid-term
Viewpoint selection:
* Optimise based on match with existing IC values.
Allow user to specify structure of model.
* Determine order in which distributions are combined.
* Specify weights for particular combinations, e.g. weighted viewpoints, or weighted memory stores.
* Multiple memory stores.
* Specify alternative context strategies.
* Provide some prepackaged models, e.g. the current model structure.
Adding viewpoint weights to output.
New basic viewpoints:
* cents - a higher resolution representation of pitch.
* comma - this needs implementing?
More flexible way for user to specify constraints on viewpoint search.
h2. Mid-term
* Allow models to use predictive information (PI), expected PI and PI rate (as analogs to IC, entropy and entropy rate respectively).
* Feature selection/generation.
h2. Long-term
* Hierarchical structure. structure?
* Parallel implementation. implementations?