Evidence map›Paper›PMID 34450731›Full record

ArticleSensors (Basel, Switzerland)2021

Intuitive Cognition-Based Method for Generating Speech Using Hand Gestures.

Eldad Holdengreber, Roi Yozevitch, Vitali Khavkin

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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

3 authors.

Eldad HoldengreberDepartment of Mechanical Engineering and Mechatronics, Ariel University, Ariel 40700, Israel.ORCID 0000-0001-5696-4384
Roi YozevitchDepartment of Computer Science, Holon Institute of Technology, Holon 58102, Israel.ORCID 0000-0001-5180-4541
Vitali KhavkinDepartment of Mechanical Engineering and Mechatronics, Ariel University, Ariel 40700, Israel.

Funding

Navigation and Accessibility Research Center of Ariel University (NARCA) RA2000000284
6 · The paper itself

Abstract

Muteness at its various levels is a common disability. Most of the technological solutions to the problem creates vocal speech through the transition from mute languages to vocal acoustic sounds. We present a new approach for creating speech: a technology that does not require prior knowledge of sign language. This technology is based on the most basic level of speech according to the phonetic division into vowels and consonants. The speech itself is expected to be expressed through sensing of the hand movements, as the movements are divided into three rotations: yaw, pitch, and roll. The proposed algorithm converts these rotations through programming to vowels and consonants. For the hand movement sensing, we used a depth camera and standard speakers in order to produce the sounds. The combination of the programmed depth camera and the speakers, together with the cognitive activity of the brain, is integrated into a unique speech interface. Using this interface, the user can develop speech through an intuitive cognitive process in accordance with the ongoing brain activity, similar to the natural use of the vocal cords. Based on the performance of the presented speech interface prototype, it is substantiated that the proposed device could be a solution for those suffering from speech disabilities.

Indexed as

GesturesSpeechCognitionHandHumansPhoneticsSign Languagecognitive sensingdepth camerahand gestures recognitioninformation entropyLeap Motion Controllermutenessspeech disabilityspeech interface

Identifiers

PMID34450731
PMCPMC8402147

What OpenQuestion holds

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LicenceCC BY
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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.