Discrimination of aspiration noise in breathy vowels
Notice bibliographique
Résumé
The amount of noise in a speech signal is typically associated with the perception of breathiness (Hillenbrand, 1998; Kreiman and Gerratt, 2005). Previous studies estimated difference limens (DLs) for discriminating a change in the amount of noise in a vowel using either adaptive procedures (Shrivastav and Sapienza, 2006) or a same-different task (Kreiman and Gerratt, 2005). In these studies, DLs for the amount of noise in a vowel were found to be about 11 to 21 dB, and depended on the noise level of the standard vowel (smaller DLs for larger amounts of noise in the standard). While previous studies co-varied the amount of noise with changes in other glottal parameters (e.g., open quotient, spectral tilt), in the present study we investigated DLs for aspiration noise by keeping other glottal parameters constant. Vowels were synthesized using the implementation of the Klatt synthesizer within the Praat software (Boersma and Weenink, 2015). Six-formant vowels /ae/ and /i/ were modeled after utterances of three male speakers selected from the Hillenbrand vowel database (Hillenbrand, Getty, Clark and Wheeler, 1995). There were six vowels in total (two vowels by three speakers). Formant and fundamental frequency estimates at eight time points within each vowel were used to synthesize the experimental stimuli using the parallel branch of the Klatt synthesizer. Glottal waveform settings for all stimuli included an open quotient of 0.4. Voicing amplitude was set to reproduce the intensity contour of the original vowels, and ranged from 67 to 73 dB (average = 70 dB). All other glottal parameters were set to default values, except for the level of the aspiration noise (AH), which was set to either 35 (standard stimuli), 37, or 39 dB. Vowel duration ranged from 276 to 302 ms (average = 290 ms). Stimuli were presented using a two-alternative forced choice (2AFC) procedure. Within each trial, listeners heard a sequence of two intervals, one containing the standard stimulus (35-dB AH level) and the other containing the comparison vowel (AH level of either 37 or 39 dB). Naive listeners participated in a short training session prior to taking part in two experimental sessions (one for /ae/, and one for /i/ stimuli). Listeners were asked to select the interval corresponding to the stimulus that sounded “breathier”. Feedback was provided after each response. Stimuli were presented binaurally through headphones at a level of 72 dBA. Responses were converted into d’ scores, a sensitivity measure based on signal detection theory (Macmillan and Creelman, 2005). As expected, sensitivity was consistently higher for the 39 dB than for the 37 dB stimuli. Differences in d’ scores were observed between the two vowels, and across the three speakers. By taking a d’ value of 1 (moderate sensitivity) as the empirical threshold estimate for a change in AH, DLs for aspiration noise were found to be 2-4 dB across the six vowels. These DLs are much smaller than those reported by previous studies. The possible reasons for the large differences in reported DLs among different studies, and the acoustic cues associated with breathiness discrimination with the present vowels, will be discussed. Boersma, P., and Weenink, D. (2015). Praat: doing phonetics by computer [Computer program]. Version 5.4.19, retrieved 22 September 2015 from http://www.praat.org/ . Hillenbrand, J., Getty, L. A., Clark, M. J., and Wheeler, K. (1995). Acoustic characteristics of American English vowels. The Journal of the Acoustical Society of America, 97 (5), 3099-3111. Kreiman, J. and Gerratt, B. R. (2005). Perception of aperiodicity in pathological voice. The Journal of the Acoustical Society of America, 117(4 Pt 1), 2201–2211. Macmillan, N. A. and Creelman, C. D. (2005). Detection Theory: A user’s giude (2 nd ed.) Mahwah, New Jersey: Lawrence Earlbaum Associates. Shrivastav, R., and Sapienza, C. M. (2006). Some difference limens for the perception of breathiness. The Journal of the Acoustical Society of America, 120 (1), 416-423.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».