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

* Polyphonic viewpoints for modelling harmonic movement
* 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

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 basic viewpoints than just cpitch, onset & bioi

h2. Modelling 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.
* Allow multiple memory stores (i.e., not restricted to just two: the LTM and STM).
* Hierarchical structure: chunk common patterns into symbols using information content and entropy as indicators of grouping structure (Pearce et al., 2010, Perception)
* Compute predictive information (PI), expected PI and PI rate as analogs

Allow user to IC, entropy and entropy rate respectively (Abdallah & Plumbley, 2009). specify structure of model.
* Offer the selection of alternative context strategies (e.g., include future context) Determine order in which distributions are combined.
* Allow the user to fix the Specify weights for particular combinations, e.g. weighted viewpoints, or weighted memory stores (LTM/STM etc.) stores.
* Allow Multiple memory stores (i.e., not restricted to just two: the user to determine order of model combination (e.g., LTM-STM first, then viewpoints vs viewpoints first then LTM/STM)

h2. Longer-term goals

Interface LTM and STM).
* A web service. Specify alternative context strategies (e.g., future context)
* Implement a 'Pace' viewpoint: measure of information rate (bits/sec), analogous to flow in speech production. 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.

Testing
** Include unit testing code.