Revising the Bantu tree.

Area of Science:

• Computational linguistics
• Historical linguistics
• Phylogenetics

Background:

• Traditional phylogenetic methods in historical linguistics rely on subjective authority, hindering empirical validation.
• Existing phylogenetic studies of Bantu languages, crucial for understanding sociocultural histories, are based on potentially unfalsifiable data.
• Comparative lexical analyses often use numerical representations of words, which can obscure underlying relationships.

Purpose of the Study:

• To apply DNA sequence optimization algorithms to analyze Bantu language relationships.
• To treat basic vocabulary as sequences of sounds for a more objective phylogenetic analysis.
• To revise the established Bantu language tree and improve inferences about historical language expansion and migration.

Main Methods:

• Utilizing algorithms adapted from DNA sequence optimization to analyze linguistic data.
• Treating basic vocabulary items as sequences of phonetic sounds.
• Comparing results with traditional methods based on numerical reductions of lexical data.

Main Results:

• The study yields finer-grained results, indicating significant revisions to the current Bantu language phylogenetic tree.
• The new method allows for more robust inferences regarding the history of Bantu language expansion and migration across sub-Saharan Africa.
• Empirical testing of "early-split" versus "late-split" hypotheses for East and West Bantu was enabled.

Conclusions:

• Phylogenetic analysis of sound sequences provides a more empirically grounded and robust method for reconstructing language histories.
• The revised Bantu language tree necessitates re-evaluation of previous sociocultural and migration models.
• This approach overcomes limitations of traditional methods reliant on subjective authority statements.