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Record W1940647742 · doi:10.1108/jat-10-2014-0026

Co-designing a speech interface for people with dysarthria

2015· article· en· W1940647742 on OpenAlexaff
Foad Hamidi, Melanie Baljko, Connie Ecomomopoulos, Nigel J. Livingston, Leonhard G. Spalteholz

Bibliographic record

VenueJournal of Assistive Technologies · 2015
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsUniversity of VictoriaYork University
Fundersnot available
KeywordsPersonalizationParticipatory designHuman–computer interactionInterface (matter)OriginalityComputer scienceDysarthriaUser interfaceModality (human–computer interaction)User experience designDomain (mathematical analysis)User interface designMultimediaEngineeringWorld Wide WebPsychologyCreativity

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to describe the development and evaluation of CanSpeak which is an open-source speech interface for users with dysarthria of speech. The interface can be customized by each user to map a small number of words they can speak clearly to commands in the computer system, thereby adding a new modality to their interaction. Design/methodology/approach – The interface was developed in two phases: in the first phase, the authors used participatory design to engage the users and their community in the customization of the system, and in the second phase, we used a more focussed co-design methodology during which a user of the system became a co-designer by directly making new design decisions about the system. Findings – The study showed that it is important to include assistive technology users and their community in the design and customization of technology. Participation led to increased engagement, adoption and also provided new ideas that were rooted in the experience of the user. Originality/value – The co-design phase of the project provided an opportunity for the researchers to work closely with a user of their system and include her in design decisions. The study showed that by employing co-design new insights into the design domain can be revealed and incorporated into the design that might not be revealed otherwise.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.743
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.321
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations8
Published2015
Admission routes1
Has abstractyes

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