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Nominal compounds (N-N) and noun-adjective (N-Adj) sequences share a distinctive morphotonology and behave as (extended) prosodic words in four Bozo languages studied. Input N and Adj stems of various tone melodies are scanned for tonal characteristics that classify the numerous melodies into just two melodic superclasses for initials. Separately, finals are also scanned and classified. The criterial tonal feature varies from language to language and from initial to final; it may be the leftmost tone element or a configuration (level versus contour). Tone overlays are then associated with the initial, the final, or both jointly. In some cases, the lexical melody of the initial is overwritten locally, but is expressed at a distance by determining or at least influencing the overlay on the final.In the neighboring isolate Bangime, a structurally similar scan-classify-overlay system is at work in definite and possessed NPs.In Bozo and Bangime, an overlaid tone pattern may differ from or even invert the (lexical) melody. However, because overlays are associated with melodic superclasses, they allow partial recovery of melodies by listeners. The scan-classify-overlay model is distinct both from ordinary tonal morphophonology (which directly operates on lexical tones) and from true replacive tonal ablaut (which irrecoverably erases melodies).
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This content will become publicly available on December 7, 2026
Chord-conditioned Melody and Bass Generation
We evaluate five Transformer-based strategies for chord-conditioned melody and bass generation using a set of music theory–motivated metrics capturing pitch content, pitch interval size, and chord tone usage. The evaluated models include (1) no chord conditioning, (2) independent line chord-conditioned generation, (3) bass-first chord-conditioned generation, (4) melody-first chord-conditioned generation, and (5) chord-conditioned co-generation. We show that chord-conditioning improves the replication of stylistic pitch content and chord tone usage characteristics, particularly for the bass-first model.
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- Award ID(s):
- 2228910
- PAR ID:
- 10657700
- Publisher / Repository:
- NeurIPS 2025 Workshop on AI for Music (AI4Music)
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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