Bol Processor grammars

James Kippen & Bernard Bel

In Mira Balaban, Otto Laske et Kemal Ebcioglu (eds.) Understanding Music with AI, American Association for Artificial Intelligence Press, Menlo Park CA (1992): 366-400.

Abstract

Bol Processor gram­mars are an exten­sion of unre­strict­ed gen­er­a­tive gram­mars allow­ing a sim­ple rep­re­sen­ta­tion of string "pat­terns", here tak­en to mean rep­e­ti­tions and homo­mor­phic trans­for­ma­tions. These have been suc­cess­ful­ly applied to the sim­u­la­tion of impro­visato­ry tech­niques in tra­di­tion­al drum music, using a production-rule sys­tem called "Bol Processor BP1". The basic con­cepts and pars­ing tech­niques of BP1 are presented.

A new ver­sion of Bol Processor, name­ly "BP2", has been designed to serve as a aid to rule-based com­po­si­tion in con­tem­po­rary music. Extensions of the syn­tac­tic mod­el, such as metavari­ables, remote con­texts, sub­sti­tu­tions and pro­grammed gram­mars, are briefly introduced.

Excerpts of an AI review of this paper (Academia, June 2025)

Overview and Summary

The authors pro­pose a for­mal­ism, called "Bol Processor gram­mars," designed to cap­ture and sim­u­late per­for­mance and impro­visato­ry behav­iors in tra­di­tion­al drum music—particularly North Indian tabla. This work presents a detailed account of how their pro­posed grammar-based sys­tem (BP1 and sub­se­quent­ly BP2) man­ages musi­cal ele­ments such as gen­er­a­tive rules, pars­ing pro­ce­dures, and higher-order trans­for­ma­tions. The authors draw on con­cepts from for­mal lan­guage the­o­ry, specif­i­cal­ly incor­po­rat­ing string rewrit­ing, gen­er­a­tive gram­mars of vary­ing types (from context-free to unre­strict­ed), and pat­tern languages.

The mono­graph not only dis­cuss­es the­o­ret­i­cal frame­works but also pro­vides imple­men­ta­tions and exam­ples rel­e­vant to com­po­si­tion, impro­vi­sa­tion, and eth­no­mu­si­co­log­i­cal analy­sis. By com­bin­ing stan­dard gram­mars with addi­tion­al fea­tures (e.g., pat­tern rules, neg­a­tive con­texts, remote con­texts, sub­sti­tu­tions, homo­mor­phisms, and a sophis­ti­cat­ed weight­ing mech­a­nism), the Bol Processor aims to mod­el cre­ative aspects of impro­visato­ry traditions.

Contribution and Significance

• The paper bridges the­o­ret­i­cal com­put­er sci­ence (rewrit­ing sys­tems, gen­er­a­tive gram­mars) with eth­no­mu­si­co­log­i­cal inquiry. This inter­dis­ci­pli­nary approach shows how lan­guage mod­els can adapt to musi­cal per­for­mance tra­di­tions, espe­cial­ly where oral trans­mis­sion prevails.
• The authors intro­duce exten­sions to clas­si­cal Chomsky hier­ar­chies by incor­po­rat­ing string pat­tern lan­guages and homo­mor­phisms specif­i­cal­ly tai­lored for music com­po­si­tion and analy­sis. This advance­ment is espe­cial­ly valu­able to those research­ing com­pu­ta­tion­al musi­col­o­gy or algo­rith­mic composition.
• By pro­vid­ing prac­ti­cal imple­men­ta­tion details and guide­lines (e.g., sub­gram­mars, weight­ing rules, context-sensitive sub­sti­tu­tions), the study con­veys a clear path for oth­ers look­ing to mod­el or sim­u­late impro­vi­sa­tion­al processes.

Strengths

• Clarity of Theoretical Underpinnings: The text care­ful­ly explains the fun­da­men­tals of gen­er­a­tive gram­mars and pat­tern lan­guages, ensur­ing that read­ers unfa­mil­iar with for­mal lan­guage the­o­ry can still fol­low the ratio­nale behind the Bol Processor model.
• Comprehensive Examples: The inclu­sion of worked-through gram­mar list­ings, detailed pars­ing traces, and real-world musi­cal seg­ments high­lights an applied per­spec­tive. Readers can see exact­ly how the rules oper­ate on con­crete musi­cal materials.
• Interdisciplinary Integration: The man­u­script thought­ful­ly weaves togeth­er com­pu­ta­tion­al lin­guis­tics, eth­no­mu­si­col­o­gy, and com­po­si­tion, offer­ing a unique per­spec­tive to each discipline.
• Generative and Analytical Capacities: Emphasizing both the gen­er­a­tion of new musi­cal vari­a­tions and the pars­ing of exist­ing per­for­mances demon­strates the system’s two-fold util­i­ty: it sup­ports cre­ative com­po­si­tion while pro­vid­ing a frame­work for empir­i­cal analysis.

Areas for Further Development

• Handling of Larger-Scale Form: While the paper address­es theme-variation struc­tures, the method­ol­o­gy could be extend­ed to more exten­sive glob­al forms or multi-sectional pieces. More elab­o­ra­tion on how the gram­mar might man­age nest­ed forms or very long struc­tures would strength­en the approach.
• Quantitative Evaluation: The text pro­vides evi­dence of suc­cess­ful mod­el­ing but could ben­e­fit from addi­tion­al dis­cus­sion of how cor­rect­ness or “musi­cal plau­si­bil­i­ty” is sys­tem­at­i­cal­ly test­ed, beyond anec­do­tal or inter­ac­tive ses­sions with experts.
• Comparisons with Other Systems: A more in-depth com­par­i­son with exist­ing com­pu­ta­tion­al music sys­tems that also employ gen­er­a­tive gram­mars (e.g., pure­ly context-free or Markov-based approach­es) might deep­en an under­stand­ing of the Bol Processor’s unique contributions.

Readability and Presentation

• The writ­ing is clear and con­sis­tent­ly struc­tured, espe­cial­ly around the dis­crete sec­tions (intro­duc­tion, pat­tern rules, pars­ing, and advanced fea­tures in BP2). Diagrams and gram­mar list­ings are help­ful, though fur­ther clar­i­fy­ing anno­ta­tions in some fig­ures could assist read­ers less famil­iar with for­mal notation.
• The appen­dices excel in pre­sent­ing extend­ed exam­ples and step-by-step pars­es, adding trans­paren­cy to the meth­ods. This style of pre­sen­ta­tion ensures repro­ducibil­i­ty and offers insights into how to adapt or mod­i­fy the sys­tem for oth­er musi­cal styles.

Potential Impact on the Field

The sys­tem has appar­ent impli­ca­tions not just for tabla and oth­er per­cus­sion tra­di­tions but for any domain where com­plex vari­a­tions can be expressed in a rule-based man­ner. Likewise, com­posers work­ing with algo­rith­mic or computer-aided com­po­si­tion may dis­cov­er a robust set of tech­niques for shap­ing vari­a­tion, tex­ture, and form. Researchers in eth­no­mu­si­col­o­gy might find new ana­lyt­i­cal tools for uncov­er­ing sys­tem­at­ic ele­ments in impro­vi­sa­tion­al practices.

Overall, the work stands as a thor­ough explo­ration of gen­er­a­tive and pars­ing approach­es tai­lored to music, illus­trat­ing how com­pu­ta­tion­al mod­els can deep­en under­stand­ing of both fixed and impro­vised musi­cal structures.

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