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Record W2038494031 · doi:10.1097/aud.0b013e31828e4dad

Envelope Following Responses Elicited by English Sentences

2013· article· en· W2038494031 on OpenAlexaff
Jong Min Choi, David W. Purcell, Julie-Anne M. Coyne, Steven J. Aiken

Bibliographic record

VenueEar and Hearing · 2013
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsDalhousie UniversityLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsVowelAudiologyDuration (music)SentenceContext (archaeology)Steady state (chemistry)MathematicsSpeech recognitionAmplitudeElectrophysiologyEnvelope (radar)Noise (video)PsychologyAcousticsMedicineComputer sciencePhysicsNatural language processingBiologyArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

In Brief Objectives: It would be clinically valuable if an electrophysiological validation of hearing aid effectiveness in conveying speech information could be performed when a device is first provided to the individual after electroacoustic verification. This study evaluated envelope following responses (EFRs) elicited by English vowels in a steady state context and in natural sentences. It was the purpose of this study to determine whether EFRs could be detected rapidly enough to be clinically useful. Design: EFRs were elicited using 5 vowels spanning the English vowel space, /i/, /ε/, /æ/, / /, and /u/. These were presented either as concatenated steady state vowels (total duration 10.04 seconds) or in three 5-word sentences (total duration 11.77 seconds), where each vowel appeared once per sentence. Single-channel electroencephalogram was recorded from vertex (Cz) to the nape of the neck for 190 and 160 repetitions of the steady state vowels and sentences, respectively. The stimuli were presented at 70 dBA SPL. The fundamental frequency (f0) track from the stimuli was used with a Fourier analyzer to estimate the EFRs to each vowel. Noise amplitudes were also calculated at neighboring frequencies. Fifteen normal-hearing subjects who were 20 to 34 years of age participated in the experiment. Results: In the analysis of steady state vowels, the mean response amplitude of /i/ was statistically the largest at 173 nV. The other 4 steady state vowels did not differ in mean response amplitude, which varied between 73 and 106 nV. In the analysis of vowels from the 3 sentences, the largest response amplitudes tended to be for /u/. Mean amplitudes for /u/ were 164, 111, and 140 nV for the words “booed,” “food,” and “Sue,” respectively. The vowel /u/ produced statistically larger responses than /i/, /ε/, and / / when grouped across words, whereas other vowels did not differ. Mean response amplitudes for the other vowel categories in the sentences varied between 82 and 105 nV. All subjects showed significant EFRs in response to the words “Bee’s” and “booed,” but only 9 subjects showed significant EFRs for “pet,” “bed,” and “Bob.” Conclusions: The authors were readily able to detect significant EFRs elicited by vowels in a steady state context and from 3 natural sentences. These results are promising as an early step in developing a clinical tool for validating that vowel stimuli are at least partially encoded at the level of the auditory brainstem. Future research will require evaluation of the technique with aided listeners, where the natural sentences are expected to be treated as typical speech by hearing aid signal-processing algorithms. It would be clinically valuable if an electrophysiological validation of hearing aid effectiveness could be performed when a device is first provided after electroacoustic verification. This study evaluated envelope following responses (EFRs) elicited by English vowels in natural sentences and a steady state context to determine whether EFRs could be detected rapidly enough to be clinically useful. The authors were able to easily detect significant EFRs elicited by vowels in both contexts. These results are promising as an early step in developing a clinical tool for validating that vowel stimuli are at least partially encoded at the level of the auditory brainstem.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.276
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations40
Published2013
Admission routes1
Has abstractyes

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