The Influence of Semantically Related and Unrelated Text Cues on the Intelligibility of Sentences in Noise
Bibliographic record
Abstract
In Brief Objectives: In two experiments with different subject groups, we explored the relationship between semantic context and intelligibility by examining the influence of visually presented, semantically related, and unrelated three-word text cues on perception of spoken sentences in stationary noise across a range of speech-to-noise ratios (SNRs). In addition, in Experiment (Exp) 2, we explored the relationship between individual differences in cognitive factors and the effect of the cues on speech intelligibility. Design: In Exp 1, cues had been generated by participants themselves in a previous test session (own) or by someone else (alien). These cues were either appropriate for that sentence (match) or for a different sentence (mismatch). A condition with nonword cues, generated by the experimenter, served as a control. Experimental sentences were presented at three SNRs (dB SNR) corresponding to the entirely correct repetition of 29%, 50%, or 71% of sentences (speech reception thresholds; SRTs). In Exp 2, semantically matching or mismatching cues and nonword cues were presented before sentences at SNRs corresponding to SRTs of 16% and 29%. The participants in Exp 2 also performed tests of verbal working memory capacity and the ability to read partially masked text. Results: In Exp 1, matching cues improved perception relative to the nonword and mismatching cues, with largest benefits at the SNR corresponding to 29% performance in the SRT task. Mismatching cues did not impair speech perception relative to the nonword cue condition, and no difference in the effect of own and alien matching cues was observed. In Exp 2, matching cues improved speech perception as measured using both the percentage of correctly reported words and the percentage of entirely correctly reported sentences. Mismatching cues reduced the percentage of repeated words (but not the sentence-based scores) compared with the nonword cue condition. Working memory capacity and ability to read partly masked sentences were positively associated with the number of sentences repeated entirely correctly in the mismatch condition at the 29% SNR. Conclusions: In difficult listening conditions, both relevant and irrelevant semantic context can influence speech perception in noise. High working memory capacity and good linguistic skills are associated with a greater ability to inhibit irrelevant context when uncued sentence intelligibility is around 29% correct. In two experiments, we examined the influence of visually presented three-word text cues on sentence perception in noise across a range of signal-to-noise ratios (SNRs), when these cues were either related or unrelated to the meaning of the sentence. Nonword cues were used as neutral baseline. Related cues improved perception relative to nonword and unrelated cues, with larger benefit obtained at lower SNRs. At low SNRs, unrelated cues slightly impaired perception relative to nonword cues. Both reading span and the ability to read partially masked text were associated with better perception after unrelated cues at a low SNR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".