Evidence map›Paper›PMID 38501923›Full record

ArticleThe Journal of the Acoustical Society of America2024

Objective intelligibility measurement of reverberant vocoded speech for normal-hearing listeners: Towards facilitating the development of speech enhancement algorithms for cochlear implants.

Lidea K Shahidi, Leslie M Collins, Boyla O Mainsah

Open access · greenAbstract read
In one paragraph

Article in The Journal of the Acoustical Society of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Lidea K ShahidiDepartment of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27701, USA.
Leslie M CollinsDepartment of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27701, USA.
Boyla O MainsahDepartment of Electrical and Computer Engineering, Duke University, Durham, North Carolina 27701, USA.
Duke University · US

Funding

Using Machine Learning to Mitigate Reverberation Effects in Cochlear ImplantsR01DC014290 · NIDCD · DUKE UNIVERSITY · PI COLLINS, LESLIE M. · 2015 to 2019
$1.5M
Leveraging Natural Language Processing for Reverberant Speech Enhancement in Cochlear ImplantsR56DC020267 · NIDCD · DUKE UNIVERSITY · PI COLLINS, LESLIE M., HANSEN, JOHN H.L. · 2023 to 2023
$174k
NIDCD NIH HHS R01 DC014290NIDCD NIH HHS R56 DC020267
6 · The paper itself

Abstract

Cochlear implant (CI) recipients often struggle to understand speech in reverberant environments. Speech enhancement algorithms could restore speech perception for CI listeners by removing reverberant artifacts from the CI stimulation pattern. Listening studies, either with cochlear-implant recipients or normal-hearing (NH) listeners using a CI acoustic model, provide a benchmark for speech intelligibility improvements conferred by the enhancement algorithm but are costly and time consuming. To reduce the associated costs during algorithm development, speech intelligibility could be estimated offline using objective intelligibility measures. Previous evaluations of objective measures that considered CIs primarily assessed the combined impact of noise and reverberation and employed highly accurate enhancement algorithms. To facilitate the development of enhancement algorithms, we evaluate twelve objective measures in reverberant-only conditions characterized by a gradual reduction of reverberant artifacts, simulating the performance of an enhancement algorithm during development. Measures are validated against the performance of NH listeners using a CI acoustic model. To enhance compatibility with reverberant CI-processed signals, measure performance was assessed after modifying the reference signal and spectral filterbank. Measures leveraging the speech-to-reverberant ratio, cepstral distance and, after modifying the reference or filterbank, envelope correlation are strong predictors of intelligibility for reverberant CI-processed speech.

Indexed as

Cochlear ImplantationCochlear ImplantsAlgorithmsHearingSpeech Intelligibility

Identifiers

PMID38501923
PMCPMC10959555
OpenAlexW4392954992

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.