Theory + Neuroscience
Integrates prosody, affective neuroscience and attention theory to justify tonal signals as early prioritization cues in cognition.
The Framework
Tonality as Attention reframes vocal tonality from a secondary acoustic feature into a first-class attention modality. It provides methodological guidance for tonal embeddings, ethical licensing (Tonalityprint™) and evaluation metrics (e.g., HASI) so AI systems can listen - and respond - with human-level attunement. A framework bridging emotion, computation and cognition through tonality.
Method + Metrics
Practical pathways for tonal embeddings, calibration corpora and attention bias modules that modulate transformer weights in multimodal models.
Ethics + IP
Tonalityprint™ outlines consent, compensation and sonic-forget mechanisms to protect vocal sovereignty and enforce ethical licensing.
The White Paper (590+ downloads)
Tonality as Attention (Version 1.0 - October 2025) is structured for researchers and product teams exploring multimodal alignment, expressive AI and human-centered voice strategies. It includes theoretical foundations, implementation pathways, evaluation proposals and recommendations for ethical deployment.
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The Dataset
TonalityPrint (Version 1.0 - January 2026) is a specialized, controlled, single-speaker prosody dataset designed for precision-tuning functional tonal intents that govern complex human conversation in voice AI systems. The corpus provides 144 human-verified audio samples across 18 utterances, each recorded in 8 parallel prosodic states: Baseline/Neutral, five core Functional Tonal Intents (Trust, Attention, Reciprocity, Empathy Resonance, Cognitive Energy)(Picard, 1997; Cutler et al., 1997), and systematically annotated Ambivalence states, treating tonal complexity as a learnable feature rather than annotation error (Cowen & Keltner, 2017; Pell & Kotz, 2011) It includes theoretical foundations, implementation pathways, evaluation proposals and recommendations for ethical fine-tuning.
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Acknowledgment
Tonality as Attention™ builds upon the foundational concept introduced in the 2017 paper “Attention Is All You Need” et al. This white paper extends the principle of selective attention from machine learning architectures to human vocal communication - exploring how prosody, tone, and emotional reciprocity may inform the next generation of multimodal alignment between human and artificial cognition.
Further Reading
Curated sources that informed this framework (selected): Vuilleumier (2005), Bahdanau et al. (2015), Vaswani et al. (2017), Schirmer & Kotz (2006), Tsai et al. (2019). Full references are in the White Paper Manuscript.
Contact & Collaboration
If you are a research lab, founder, brand, or studio exploring tone-aware AI, dataset licensing, or advisory engagements, Ronda is available for strategic partnerships and high-impact advisory. Premium engagements and limited lab partnerships are available - contact for rates and scopes.
Email (direct): ronda@tonalityasattention.com
General: hello@tonalityasattention.com
Prefer an intro? Please use the subject line: Tonality Lab Partnership - White Paper Review for direct routing.