Abstract
The reducing effect (Bybee, 2003) is a common mechanism of phonetic change in language, causing frequent constructions to become phonetically reduced over time (e.g. I donât know becomes dunno). High-frequency constructions especially are said to reduce faster and more strongly due to âneuromotor automationâ (Bybee, 2006, p. 5). Corpus studies show reduction empirically, but cannot explain how communication remains successful despite the phenomenon. We do not know, for example, what requirements keep language users from reducing âtoo farâ, avoiding communicative chaos.
To find these requirements, we built a computer simulation with virtual speakers (âagentsâ). Each agent has a memory of constructions represented as vectors (cfr. Baevski et al., 2020). During communication, these are compared on the basis of phonetic distance to determine what construction was âheardâ. To simulate acoustic reduction, speakers can reduce an exemplarâs vector, leading to sparser representations over time.
We show that two requirements are necessary for successful reduction (i.e. reduction that is strongest, but never overly strong, in high-frequency constructions). First, the frequency distribution of constructions must be Zipfian, else the acoustic space will fail to be distributed efficiently among constructions. Second, when applying reduction, speakers should check if they are able to understand their reduced utterance themselves (âre-entrance,â Steels, 2003). Without this check, speakers reduce too far, with mass confusion as a consequence.
Our simulation shows that there might be more to the reduction principle than just a link between usage and sparsity, as certain properties inherent to language (Zipfian distribution, inner voice) are indispensable in our model world. An experimental spin-off could help confirm this.
References
Baevski, A., Zhou, H., Mohamed, A., & Auli, M. (2020). wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations. arXiv. https://doi.org/10.48550/arXiv.2006.11477
Bybee, J. (2003). Phonology and Language Use. Cambridge University Press.
Bybee, J. (2006). From Usage to Grammar: The Mindâs Response to Repetition. Language, 82(4), 711â733. https://doi.org/10.1353/lan.2006.0186
Steels, L. (2003). Language re-entrance and the âinner voiceâ. Journal of Consciousness Studies, 10(4-5), 173â185.
To find these requirements, we built a computer simulation with virtual speakers (âagentsâ). Each agent has a memory of constructions represented as vectors (cfr. Baevski et al., 2020). During communication, these are compared on the basis of phonetic distance to determine what construction was âheardâ. To simulate acoustic reduction, speakers can reduce an exemplarâs vector, leading to sparser representations over time.
We show that two requirements are necessary for successful reduction (i.e. reduction that is strongest, but never overly strong, in high-frequency constructions). First, the frequency distribution of constructions must be Zipfian, else the acoustic space will fail to be distributed efficiently among constructions. Second, when applying reduction, speakers should check if they are able to understand their reduced utterance themselves (âre-entrance,â Steels, 2003). Without this check, speakers reduce too far, with mass confusion as a consequence.
Our simulation shows that there might be more to the reduction principle than just a link between usage and sparsity, as certain properties inherent to language (Zipfian distribution, inner voice) are indispensable in our model world. An experimental spin-off could help confirm this.
References
Baevski, A., Zhou, H., Mohamed, A., & Auli, M. (2020). wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations. arXiv. https://doi.org/10.48550/arXiv.2006.11477
Bybee, J. (2003). Phonology and Language Use. Cambridge University Press.
Bybee, J. (2006). From Usage to Grammar: The Mindâs Response to Repetition. Language, 82(4), 711â733. https://doi.org/10.1353/lan.2006.0186
Steels, L. (2003). Language re-entrance and the âinner voiceâ. Journal of Consciousness Studies, 10(4-5), 173â185.
Publication type
Presentation
Presentation
DvdF25_Sevenants_etal.pdf
(73.83 KB)
Year of publication
2025
Conference location
Utrecht
Conference name
Dag van de Fonetiek 2025
Publisher
Nederlandse Vereniging voor Fonetische Wetenschappen