Evidence map›Paper›PMID 33364678›Full record

ReviewSeminars in hearing2020

Behavioral Validation of the Smartphone for Remote Microphone Technology.

Stephanie Tittle, Linda M Thibodeau, Issa Panahi, Serkan Tokgoz, Nikhil Shankar, Gautam Shreedhar Bhat, Kashyap Patel

Open access · greenAbstract readReview
In one paragraph

Review in Seminars in hearing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Smartphone-based single-channel speech enhancement application for hearing aids.The Journal of the Acoustical Society of America · 2021
    Article
  2. Review
  3. A Hearing Test Simulator GUI for clinical testing of speech recognition.Proceedings of meetings on acoustics. Acoustical Society of America · 2018
    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

7 authors at 1 institution in 1 country.

Stephanie TittleDepartment of Speech, Language, and Hearing Science, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas.
Linda M ThibodeauDepartment of Speech, Language, and Hearing Science, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, Texas.
Issa PanahiDepartment of Computer Science, School of Engineering, University of Texas at Dallas, Richardson, Texas.
Serkan TokgozDepartment of Computer Science, School of Engineering, University of Texas at Dallas, Richardson, Texas.
Nikhil ShankarDepartment of Computer Science, School of Engineering, University of Texas at Dallas, Richardson, Texas.
Gautam Shreedhar BhatDepartment of Computer Science, School of Engineering, University of Texas at Dallas, Richardson, Texas.
Kashyap PatelDepartment of Computer Science, School of Engineering, University of Texas at Dallas, Richardson, Texas.
The University of Texas at Dallas · US

Funding

Smartphone-Based Open Research Platform for Hearing Improvement StudiesR01DC015430 · NIDCD · UNIVERSITY OF TEXAS DALLAS · PI PANAHI, ISSA · 2016 to 2020
$1.9M
NIDCD NIH HHS R01 DC015430
6 · The paper itself

Abstract

As part of a National Institutes of Health-National Institute on Deafness and Other communication Disorders (NIH-NIDCD)-supported project to develop open-source research and smartphone-based apps for enhancing speech recognition in noise, an app called Smartphone Hearing Aid Research Project Version 2 (SHARP-2) was tested with persons with normal and impaired hearing when using three sets of hearing aids (HAs) with wireless connectivity to an iPhone. Participants were asked to type sentences presented from a speaker in front of them while hearing noise from behind in two conditions, HA alone and HA + SHARP-2 app running on the iPhone. The signal was presented at a constant level of 65 dBA and the signal-to-noise ratio varied from -10 to +10, so that the task was difficult when listening through the bilateral HAs alone. This was important to allow for improvement to be measured when the HAs were connected to the SHARP-2 app on the smartphone. Benefit was achieved for most listeners with all three manufacturer HAs with the greatest improvements recorded for persons with normal (33.56%) and impaired hearing (22.21%) when using the SHARP-2 app with one manufacturer's made-for-all phones HAs. These results support the continued development of smartphone-based apps as an economical solution for enhancing speech recognition in noise for both persons with normal and impaired hearing.

Indexed as

hearing aidshearing impairedremote microphone technologysmartphone

Identifiers

PMID33364678
PMCPMC7744168
OpenAlexW3111895827

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.