Roadmap¶

Installation¶

• Remove absolute pathname in connect-to-database. (mtp-admin/music-data.lisp)
• Create cache directories if they don't exist.

Data import¶

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

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

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

Testing¶

• Include unit testing code.

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 using information content and entropy as indicators of grouping structure (Pearce et al., 2010, Perception)

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 (i.e., not restricted to just two: the LTM and STM).
• 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.