IDyOM Project

h1. Roadmap

h2. Installation

* -Remove absolute pathname in connect-to-database. (mtp-admin/music-data.lisp)-

* Create cache directories if they don't exist.

h2. Data import

* -It is possible to import empty datasets, which cause an error when described.-

h2. Viewpoints

* Zero barlengths sometimes cause divide by zero errors

* A straightforward language for specifying viewpoints, including viewpoint schemas (e.g. interval, interval size), making system more data agnostic

* Polyphonic viewpoints

h2. Viewpoint selection

* Memory errors sometimes occur with large viewpoints sets (e.g., Cpitch with no basis specified)

* When decimal places are restricted for comparison, earlier systems are preferred within a round, so use full precision to choose between ties

* Print trace information about VP sets being tested + mean IC values; record this to log file.

* Optionally specify: 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

* Provide recommended viewpoints for more than just cpitch, onset & bioi

h2. Testing

* Include unit testing code.

h1. Longer-term goals

* 'Pace' viewpoint: measure of information rate (bits/sec), analogous to flow in speech production.

* A web service.

* Compute predictive information (PI), expected PI and PI rate (as analogs to IC, entropy and entropy rate respectively).

* Predict over more than one dataset.

* Hierarchical structure: chunk common patterns into symbols.

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 (e.g., future context)

* Provide some prepackaged models, e.g. the current model structure.

Efficiency:

** Check/extend caching of models etc.

** Use sampling to estimate mean IC during VP selection.

** Optimise viewpoint selection based on match with existing IC values.