Audio-visual identification of place of articulation and voicing in white and babble noise
Bibliographic record
Abstract
Research shows that noise and phonetic attributes influence the degree to which auditory and visual modalities are used in audio-visual speech perception (AVSP). Research has, however, mainly focused on white noise and single phonetic attributes, thus neglecting the more common babble noise and possible interactions between phonetic attributes. This study explores whether white and babble noise differentially influence AVSP and whether these differences depend on phonetic attributes. White and babble noise of 0 and -12 dB signal-to-noise ratio were added to congruent and incongruent audio-visual stop consonant-vowel stimuli. The audio (A) and video (V) of incongruent stimuli differed either in place of articulation (POA) or voicing. Responses from 15 young adults show that, compared to white noise, babble resulted in more audio responses for POA stimuli, and fewer for voicing stimuli. Voiced syllables received more audio responses than voiceless syllables. Results can be attributed to discrepancies in the acoustic spectra of both the noise and speech target. Voiced consonants may be more auditorily salient than voiceless consonants which are more spectrally similar to white noise. Visual cues contribute to identification of voicing, but only if the POA is visually salient and auditorily susceptible to the noise type.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".