Evidence map›Paper›PMID 41730136›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2026

A Speech-Segregation Algorithm for Spatial Hearing Aids to Operate With Multiple Sound Sources.

Jakeh E Orr, Atra Z Eslami Boudreaux, Irmak Gokcen, Yan Gai

Abstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Jakeh E OrrBiomedical Engineering Department, School of Science and Engineering, Saint Louis University, MO.ORCID 0009-0004-8280-6143
Atra Z Eslami BoudreauxBiomedical Engineering Department, School of Science and Engineering, Saint Louis University, MO.
Irmak GokcenBiomedical Engineering Department, School of Science and Engineering, Saint Louis University, MO.
Yan GaiBiomedical Engineering Department, School of Science and Engineering, Saint Louis University, MO.ORCID 0000-0002-1228-8705

Funding

Speech Localization and Enhancement for Next-Generation Hearing DevicesR15DC021563 · NIDCD · SAINT LOUIS UNIVERSITY · PI GAI, YAN · 2024 to 2024
$452k
NIDCD NIH HHS R15 DC021563
6 · The paper itself

Abstract

purposeHearing-aid users often face challenges in noisy environments due to time, level, and spectral cues being compromised by current generation hearing aids. This study explored a physiologically based speech-segregation algorithm that selectively removes or attenuates unwanted sound sources.

methodIn our previously developed localization algorithm, the time-frequency responses after a unique normalization approach always reside inside the unit circle of the model space. Given the "sparseness" property of daily sound, the model forms distinct clusters that correspond to the source locations. In the present study, the localization model was adapted to segregate speech by using a binary mask to remove the cluster of unwanted sound. The speech target was one of 200 intelligible sentences. The interfering sound was time-reversed sentences in a random sequence spoken by the same speaker. Automatic speech recognition transcribed the sound mixture before and after the segregation algorithm.

resultsWhen both target and noise were located at the front, applying a hard mask (i.e., 1 or 0) almost perfectly removed the energy of noise. When the sound sources moved to the side or back with smaller angular separations, clusters were less distinguishable, leading to worse intelligibility performance. Applying a soft mask (i.e., 1 or 0.2) instead showed slightly lower performance for the front but improved performance for the back and side.

conclusionOur algorithm performs localization and segregation in a combined and straightforward manner, potentially for spatial hearing aids to function better in challenging listening environments.

Indexed as

AlgorithmsHearing AidsSound LocalizationSpeech PerceptionHumansNoisePerceptual MaskingSpeech Intelligibility

Identifiers

PMID41730136
PMCPMC13086198

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.