The Influence of Semantically Related and Unrelated Text Cues on the Intelligibility of Sentences in Noise
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».