Interleaved lexical and audiovisual information can retune phoneme boundaries.

Interleaved lexical and audiovisual information can retune phoneme boundaries.

Ullas, Shruti;Formisano, Elia;Eisner, Frank;Cutler, Anne;
attention, perception & psychophysics 2020
149
ullas2020interleavedattention

Abstract

To adapt to situations in which speech perception is difficult, listeners can adjust boundaries between phoneme categories using perceptual learning. Such adjustments can draw on lexical information in surrounding speech, or on visual cues via speech-reading. In the present study, listeners proved they were able to flexibly adjust the boundary between two plosive/stop consonants, /p/-/t/, using both lexical and speech-reading information and given the same experimental design for both cue types. Videos of a speaker pronouncing pseudo-words and audio recordings of Dutch words were presented in alternating blocks of either stimulus type. Listeners were able to switch between cues to adjust phoneme boundaries, and resulting effects were comparable to results from listeners receiving only a single source of information. Overall, audiovisual cues (i.e., the videos) produced the stronger effects, commensurate with their applicability for adapting to noisy environments. Lexical cues were able to induce effects with fewer exposure stimuli and a changing phoneme bias, in a design unlike most prior studies of lexical retuning. While lexical retuning effects were relatively weaker compared to audiovisual recalibration, this discrepancy could reflect how lexical retuning may be more suitable for adapting to speakers than to environments. Nonetheless, the presence of the lexical retuning effects suggests that it may be invoked at a faster rate than previously seen. In general, this technique has further illuminated the robustness of adaptability in speech perception, and offers the potential to enable further comparisons across differing forms of perceptual learning.

Citation

ID: 86202
Ref Key: ullas2020interleavedattention
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
86202
Unique Identifier:
10.3758/s13414-019-01961-8
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet