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Record W2085135995 · doi:10.1097/aud.0b013e318157670a

Evaluation of the Desired Sensation Level [Input/Output] Algorithm for Adults with Hearing Loss: The Acceptable Range for Amplified Conversational Speech

2007· article· en· W2085135995 on OpenAlexaff
Lorienne M. Jenstad, Marlene Bagatto, Richard C. Seewald, Susan Scollie, Leonard E. Cornelisse, Ron Scicluna

Bibliographic record

VenueEar and Hearing · 2007
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of British ColumbiaHuntington Society of CanadaWestern University
Fundersnot available
KeywordsAudiologyLoudnessHearing aidSensationHearing lossRange (aeronautics)Sensorineural hearing lossEar canalSpeech perceptionComputer scienceSpeech recognitionPsychologyMedicinePerceptionEngineering

Abstract

fetched live from OpenAlex

In Brief Objectives: This study had two related purposes: first, to define the range of optimal ear canal levels of aided speech in both high frequency and low frequency regions for adults, using both subjective and objective definitions of optimal; and second, to determine whether a prescribed frequency response, such as that given by Desired Sensation Level [Input/Output], falls within the adult listener's optimal range. Design: Twenty-three adult listeners with mild to moderately severe sensorineural hearing loss were selected from a pool of research volunteers. They were fitted in the laboratory with the Siemens Signia hearing instrument and tested with 20 nominally different frequency responses. All advanced processing options of the hearing instrument were disabled. Subjective ratings of loudness and quality and objective measures of consonant identification were obtained for every frequency response. Results: These adult listeners had, on average, a 10 dB range of measured responses in both the low and the high frequencies that resulted in optimal performance on all the measurements. The range did not vary with degree or configuration of hearing loss, or previous hearing aid experience. Desired-Sensation-Level Input/Output targets were within the optimal range for the low frequencies, and 3 dB above the optimal range for the high frequencies. Conclusions: A range of aided ear canal frequency responses was determined within which adults with mild to moderately severe hearing loss performed optimally on both objective and subjective outcomes. Clinical implications of this finding include the following: prescriptive methods providing different targets may all result in optimal fittings; and a range of targets may be more appropriate than a single target when setting the frequency-gain characteristics of the hearing instrument. The DSL[i/o] hearing instrument prescription method was evaluated for its acceptability for adult listeners; specifically, whether the prescribed frequency response optimally amplified average speech. Twenty-three adults with mild to moderately severe sensorineural hearing loss were fitted with a commercially available hearing aid with most features disabled. Speech intelligibility, loudness, and quality measures were taken at the prescribed frequency response and alternate frequency responses. Any differences between the subject's optimal response and the prescribed response were calculated in real-ear SPL. A range of optimal settings was found. These results and their implications for changes to the DSL prescription are discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
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)0.0010.000

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 head0.160
GPT teacher head0.332
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations30
Published2007
Admission routes1
Has abstractyes

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