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Index

Published online by Cambridge University Press:  31 August 2023

Meng Ji ,
Pierrette Bouillon  and
Mark Seligman
Meng Ji
Affiliation:
University of Sydney
Pierrette Bouillon
Affiliation:
Université de Genève
Mark Seligman
Affiliation:
Spoken Translation Technology

Summary

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Type
Chapter
Information
Translation Technology in Accessible Health Communication , pp. 212 - 222
Publisher: Cambridge University Press
Print publication year: 2023
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NC
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC 4.0 https://creativecommons.org/cclicenses/

Index

AAC. See Augmentative and Alternative Communication (AAC)
Abstraction, 22
Accultran, 71
Acosta-Vargas, P., 177–178
Adaptability, 5–7. See also Pictographs
Alajarmeh, N., 177–178
Allophones, 14
Amazon Mechanical Turk (MTurk), 133
American Sign Language (ASL), 157, 178
Andreu-Valls, M., 181
Anxiety disorders, cultural and linguistic bias regarding, 101–102, 118, 119–121, 122
Apple, 72
Apple Watch, 53
AR (Augmented Reality), 54
Arassac, 131–133, 135–137, 142–143, 144
ASL (American Sign Language), 157, 178
ASR. See automatic speech recognition (ASR)
ASURA system, 23–24
ATLAS system, 24–
Augmentative and Alternative Communication (AAC), 131–133, 135–136, 147
Augmented Reality (AR), 54
Australia
National Accreditation Authority for Translators and Interpreters (NAATI), 2
sign language translation tools in, 157
automatic speech recognition (ASR)
classical ASR, 11
in Converser for Healthcare, 62, 64–65
directions in, 13
Hidden Markov models, 11
issues in, 12
language models, 11
neural ASR, 12
samples
generally, 43
iPhone Native ASR, 44
Microsoft Word (Windows 10), 44
Viterbi algorithms, 11
Babbel, 53
BabelDr
generally, 5–6, 129
customizability of, 56–57
as healthcare application, 56–57
low-resource languages and, 6
offline preparation of output in, 48
pictographs (See Pictographs)
reliability of, 56
Speech2sign version, 164
Swiss-French Sign Language (LSF-CH) (See Swiss-French Sign Language (LSF-CH))
Back-translation, 49
Bayesian classifiers. See Relevance vector machines (RVMs)
Berners-Lee, Tim, 187–188, 200
BERT language model, 34
Bias. See Cultural and linguistic bias
Bi-directional speech approaches in healthcare applications
generally, 57–58
Accultran, 71
Converser for Healthcare (See Converser for Healthcare)
English-Portuguese SLT, 71
Fujitsu (See Fujitsu Laboratories, Ltd.)
Google Translate, 57
Jibbigo, 71
MASTOR, 71
MedSLT, 71
surveys, 71
Translation Shortcuts (See Translation Shortcuts)
Binggeli, Tatjana, 153–154
Blind and visually impaired (BVI) persons
accessibility of healthcare websites by, 178
multilingual healthcare website accessibility by, 181–182
Bluetooth, 53
Brajnik, G., 187
Brooke, J., 140
Bureau of Internet Accessibility, 184
BVI (Blind and visually impaired) persons
accessibility of healthcare websites by, 178
multilingual healthcare website accessibility by, 181–182
Canada, accessibility of healthcare websites in, 177
Canopy, 72, 129
Cantero, Odile, 153–154
Carnegie Mellon University, 9170, 52
Carol Davila University of Medicine and Pharmacy (Bucharest), 158
Casalegno, E., 181–182
CDFA-2 (Clinical Document Architecture), 71
Cheetah, 53
Chrome DevTools, 184
Clarke, Arthur C., 74
Classical ASR, 11
Clinical Document Architecture (CDA-2), 71
Cloud computing, 54
CNNs (Convolutional Neural Networks), 35–36
Coarticulation, 14
Cod.eX, 201
Concatenative TTS
generally, 13–14
allophones, 14
coarticulation, 14
extra-prosodic speech features, 15
lexical disambiguation, 14–15
normalization, 15
pronunciation problems, 15
prosody, 15
Convention on the Rights of Persons with Disabilities (UNCRPD), 156
Converser for Healthcare
generally, 7, 58
automatic speech recognition (ASR) in, 62, 63–65
Change Meaning window, 64
Earring icon, 50, 62, 63, 64–65
evaluation of, 61
feedback, 59
lexical disambiguation, 59
machine translation (MT) in, 62
Meaning Cues window, 59, 64
multimodal input, 60–61
NoPrecheck mode, 62, 64–65
pilot project, 61
Precheck mode, 62
revised system, 61–65
surveys, 71
system description, 58–60
Traffic Light icon, 50, 62, 63–65
Translation Shortcuts (See Translation Shortcuts)
Convolutional Neural Networks (CNNs), 35–36
C-STAR, 25
Cultural and linguistic bias
generally, 100–102
anxiety disorders, negativity toward, 101–102, 118, 119–121, 122
back-translations with negative connotations, 122
data collection
generally, 102–103
information accessibility and, 102–103
information credibility and, 103
topic relevance and, 102
understandability and, 103
user relevance and, 103
feature optimization
figures, 105–107
lexical dispersion rate features, 107–108
lexical frequency band features, 108
semantic features, 108
feature set descriptions, 124–126
gender bias, 100–101
Google Translate (GT) and, 104, 120
health information websites, 127–128
Mann Whitney U test, 112, 126–127
mean AUC, 115, 117
paired sample t tests
high-performing classifiers, 117–
sensitivity difference, 114
specificity difference, 114, 115–
racial bias, 100–101
relevance vector machines (RVMs)
combined, separately optimized versus full features sets, 113
development of classifiers, 104, 120
empirical results generally, 120
high-sensitivity classifiers, 118–119
high-specificity classifiers, 118, 119
jointly optimized versus full features sets, 112–
separately optimized versus full features sets, 111–
training and testing datasets, 104
variation of AUC, 115, 116
Culturally and Linguistically Diverse (CALD) Assist, 72, 129
Deaf community
generally, 3
access to healthcare, importance of, 153–154
improvements in healthcare communication, 154
inclusivity for, 7–8
increase in hearing impairment, 7
sign language (See Sign language)
Swiss-French Sign Language (LSF-CH) and, 153, 154 (See also Swiss-French Sign Language (LSF-CH))
in Switzerland
generally, 154
access to healthcare by, 153–154
legal framework, 154–155
sign language, 154–155
DeepL Translator, 35–36, 45–46, 56, 70
Deque Systems, 187
Detectability of errors, 4–5. See also Prediction of errors
DGS (German Sign Language), 157–158
DictaSign, 161
Dillinger, Mike, 61
Disabilities, people with. See People with disabilities (PwD)
Distributional hypothesis, 27
Doodle Health, 133
Dr. Passport, 129
DuoChart, 72
Dutch Sign Language (NGT), 158
Earbuds, 53
Encoder layers, 36–38
English-Portuguese SLT, 71
Equality of access to healthcare information
generally, 8–9, 176, 202
abstract, 175
accessibility of healthcare websites, 176–178
barriers to
generally, 8, 197
accessibility knowledge, lack of, 197–198
localization knowledge, lack of, 197
web authoring tool settings, varied access to, 198
challenges in evaluation
generally, 198
accessibility enablers with interdisciplinary background, need for, 200–201
automated audits, 198–199
compliance criteria, defining, 199–200
empirical results
accessibility errors, 189
language of page, 191–192
limitations of, 201
title of page, 192–193
future research, 202
Google Translate and, 183
on Internet generally, 175
language of page
empirical results, 191–192
as feature studied, 186
language values used, 192
percentage of pages per language meeting compliance criteria, 191–192
localization of healthcare websites, 178–180
multilingual healthcare website accessibility, 180–182
organizations, list of, 209
study methodology
generally, 182–183
data selection, 183–184
language of page, 186
language values used, 192
testing methods, 184–185
title of page, 187–189
title of page
abbreviations without expanded form, absence of, 195
compliance criteria, 193
empirical results, 192–193
as feature studied, 187–189
identification of subject, 194
localized title differing from original title, 195–196
original and target language, text not in both, 196
percentage of pages per language meeting compliance criteria, 192–193
repetitions, absence of, 194–195
sense when read out of context, 194
shortness of title, 193
target language, text in, 196
types of errors, 193
URL addresses, absence of, 195
websites, list of, 209
eSIGN, 161
Facebook, 31, 52
Feedback, 49, 59
Firth, John Rupert, 27
Fixed-phrase approaches in healthcare applications
generally, 55, 129–130
Canopy, 72
DuoChart, 72
MavroEmergency Medical Spanish, 72
MediBabble, 72
MedSpeak, 72
Phraselator, 55–56
S-MINDS, 55–56
surveys, 72
Universal Doctor, 72
Flesch Reading Ease Score, 89–93
Fluential, 55, 56
Françoise avatar, 161
French Belgian Sign Language (LSFB), 164–166, 167
Fujitsu Laboratories, Ltd.
generally, 58, 67–68
actual trials, 69
Artificial Intelligence Laboratory, 53, 67
clinical trials, 68–69
design preparation, 68
future commercialization and deployment, 69
simulation tests, 68
wearables, 69
German Sign Language (DGS), 157–158
Gestural Signing Gesture Markup Language (G-SigML), 161–164
Google, 28–29, 31
Google Lighthouse, 184, 185, 188, 189, 191
Google Translate (GT)
cultural and linguistic bias and, 104, 120
equality of access to healthcare information and, 183
as healthcare application, 57, 59
neural machine translation (NMT) and, 78
prediction of errors and, 81, 82, 83, 85, 94
GPT-3, 32, 35
G-SigML (Gestural Signing Gesture Markup Language), 161–163
GT. See Google Translate (GT)
Gunning Fox Index, 89–93
Hamburg Notation System for Sign Languages (HNS), 161
Hanson, V. L., 199
Healthcare applications
generally, 47, 54–55, 73–74
abstract, 47
bi-directional speech approaches (See Bi-directional speech approaches in healthcare applications)
caveats, 73–74
customization of
generally, 51
Augmented Reality (AR), 54
cloud computing, 54
data security, 54
earbuds, 53
laptops, 53
peripherals, 53–54
platforms, 51–53
smartphones, 53
tablets, 53
wearables, 53
fixed-phrase approaches (See Fixed-phrase approaches in healthcare applications)
hybrid approaches, 55
reliability of
generally, 48
as accuracy plus confidence, 48
back-translation, 49
correction, 49–50
feedback, 49
offline preparation of output, 48–49
record-keeping, 51
studies, 70
translation memory, 48–49
surveys
generally, 71
bi-directional speech approaches, 71
fixed-phrase approaches, 72
representative apps, 72–73
Hidden Markov models, 11
HiFi-GAN, 17
Hill, B., 131
HNS (Hamburg Notation System for Sign Languages), 161
HospiSign, 158–159
IBM, 25, 59, 71
ICESCR (International Covenant on Economic, Social and Cultural Rights), 156
IDEA principles
generally, 3
adaptability, 5–7 (See also Pictographs)
detectability of errors, 4–5 (See also Prediction of errors)
equality of access, 8–9 (See also Equality of access to healthcare information)
inclusivity, 7–8 (See also Swiss-French Sign Language (LSF-CH))
IETF. See Internet Engineering Task Force (IETF)
IF (Interchange Format), 25
IHG Translator App, 53
ili, 53
Importance of accessibility, 1–3
Inclusivity, 7–8. See also Swiss-French Sign Language (LSF-CH)
Interchange Format (IF), 25
International Covenant on Economic, Social and Cultural Rights (ICESCR), 156
Internet, access to healthcare information on. See Equality of access to healthcare information
Internet Engineering Task Force (IETF), 186
iPhone Native ASR, 44
iPhones, 52
Iran, accessibility of healthcare websites in, 177–178
Ishida, R., 186
Italy
accessibility of healthcare websites in, 177
sign language translation tools in, 157
iTranslate, 53
Japan
Global Communication Plan Project, 67
National Institute of Information and Communications Technology (NICT), 68
JASigning avatar, 158, 161–164
Ji, Meng, 73
Jibbigo, 56, 71
Jiménez-Crespo, M.Á., 178–180, 181, 183, 197
Kaiser Permanente, 58, 61
Kassam, R., 133
Katz, M. G., 131
Kerremans, K., 129
Kim, H., 133
Korea, accessibility of healthcare websites in, 178
Kushalnagar, P., 178
Lancaster Semantic Annotation System (USAS), 84, 103
Language models, 11
Laptops, 53
Large Language Models (LLMs), 34, 35
Lexical disambiguation, 14–15, 23, 59
Limited literacy/educational attainment, 3
Linguistic bias. See Cultural and linguistic bias
Linguistic Inquiry and Word Count System (LIWC), 104
LiteDevTool, 169
LIWC (Linguistic Inquiry and Word Count System), 104
LLMs (Large Language Models), 34, 35
LSFB, 170
LSFB (French Belgian Sign Language), 164–166, 167
LSR (Romanian Sign Language), 158
Lüchtenberg, M., 178
Machine translation (MT)
generally, 17–18, 130
based on fixed phrases, 18
beyond fixed phrases, 18
in Converser for Healthcare, 62
neural machine translation (NMT) (See Neural machine translation (NMT))
rule-based MT (See Rule-based machine translation)
statistical machine translation (SMT), 25–28
vector-based semantics, 26–28
Marcos, M.-C., 181
MASTOR, 25, 59, 71
MavroEmergency Medical Spanish, 72
MediBabble, 72, 129, 154
Medical Signbank, 157
Medipicto AP-HP, 133–134
MedlinePlus, 183
MedSLT, 71
MedSpeak, 72
Meta, 31
Microsoft, 59
Microsoft Translator, 53
Microsoft Word (Windows 10), 44
Minacapilli, C. A., 182, 197
Moore’s Law, 11
MSD Manuals, 80–81
MT. See machine translation (MT)
MTurk (Amazon Mechanical Turk), 133
Multiculturalism, 1–2
Multilingualism, 1–2
Musleh, Ahmad, 71, 72
My Symptoms Translator, 133–134
Nagase, Tomoki, 67
Netherlands
Deaf community, access to healthcare by, 153–154
sign language translation tools in, 158
Neural ASR, 12
Neural machine translation (NMT)
generally, 28–32
conceptual introduction, 29–30
cultural and linguistic bias in (See Cultural and linguistic bias)
Google Translate (GT) and, 78
hidden learning, 30–31
prediction of errors and, 78
transformers (See Transformers)
“zero-shot” NMT, 31
Neural TTS
generally, 16
control points, absence of, 17
insufficient training data, 17
neural vocoders, 17
pronunciation problems, 17
prosody, 17
time and computation required, 17
Neural vocoders, 17
NGT (Dutch Sign Language), 158
NMT. See Neural machine translation (NMT)
Normalization, 15
Nuance, Inc., 59
Oleander Software, 83
Paradigms, 18
Parmanto, B., 177
People with disabilities (PwD)
blind and visually impaired (BVI) persons
accessibility of healthcare websites by, 178
multilingual healthcare website accessibility by, 181–182
Deaf community (See Deaf community)
prevalence of, 2–3
unmet needs for healthcare information, 175–176
Phraselator, 55–56
Pictographs
generally, 6, 129–130, 148
abstract, 129
Arassac, 131–133, 135–137, 142–143, 144
bi-directional interface, 134–135
comprehensibility
previous study, 136–137
in usability study, 145, 147
crowdsourcing and, 133
expandability of content, 138–139
limited availability of, 133–134
medical communication, use in, 131–134
Medipicto AP-HP, 133–134
My Symptoms Translator, 133–134
patient satisfaction study
generally, 130, 147
empirical results, 140–142
limitations of, 147–148
study design, 138–140
response editor, 138–139
SantéBD, 131, 132
Sclera, 131–133, 135–137, 142–143, 144
selection of, 135–137
usability study
generally, 130, 147
comprehensibility, 145, 147
device used, effect of, 147
empirical results, 145
limitations of, 147–148
number of choices, effect of, 145, 147
order of choices, effect of, 146–147
response time, 145–146
study design, 142–144
USP, 131
Visualisation of Concepts in Medicine (VCM), 131
Widgit Health, 131
Piller, I., 179
Pisourd, 157, 159
Pitch Synchronous Overlap and Add (PSOLA), 15
Pockettalk, 53
Pontus, V., 182, 197
Prediction of errors
generally, 5, 78–80, 96–97
abstract, 78
annotation of features, 83–84
Bayesian classifiers (See Relevance vector machines (RVMs))
conceptual mistakes in machine translation, 82–83
Google Translate (GT) and, 81, 82, 83, 85, 94
infectious diseases and, 81
joint feature optimization, 87
labelling of machine translations, 81
neural machine translation (NMT) and, 78
prevalence of conceptual mistakes, 83
relevance vector machines (RVMs) and (See Relevance vector machines (RVMs))
research hypothesis, 80
screening criteria, 80–81
separate feature optimization, 86–87
sources of errors, 79
Prosody, 15, 17
PSOLA (Pitch Synchronous Overlap and Add), 15
PwD. See People with disabilities (PwD)
Rahmatizadeh, S., 177–178
Readability Studio, 83
Recurrent Neural Networks (RNNs), 33, 34
Recursive Feature Elimination with SVM (RFE-SVM), 86
Relevance vector machines (RVMs)
cultural and linguistic bias and
combined, separately optimized versus full features sets, 113
development of classifiers, 104, 120
empirical results generally, 120
high-sensitivity classifiers, 118–119
high-specificity classifiers, 118, 119
jointly optimized versus full features sets, 112–
separately optimized versus full features sets, 111–
prediction of errors and
generally, 79, 80, 84–85
backward feature elimination, 86
classifier optimization, 85–86
combined features via separate optimization (CFSO), 88–89, 91, 95, 96
comparison with binary classifiers, 89–93
error-prone English text (EPET), 93–94
Flesch Reading Ease Score, 89–93
Gunning Fox Index, 89–93
jointly optimized structural and semantic features (CFJO), 88–89
non-error-prone English text (non-EPET), 93–94
optimized semantic features (OSF), 88–89
optimized structural features (OTF), 88–89
paired-sample area difference under ROC curves, 92–93
percentage of texts assigned to 10% probability bins, 93–94
performance using different feature sets on test dataset, 88–89
positive likelihood ratio (LR+), 95–96
probability thresholds, 95
readability formulas, 90
Recursive Feature Elimination with SVM (RFE-SVM), 86
sensitivity-specificity pairs, 95
SMOG Index and, 89–93
support vector machines (SVMs) contrasted, 93
testing and training, 85
RFE-SVM (Recursive Feature Elimination with SVM), 86
Richards, J. T., 199
Right to health, 155–157
RNNs (Recurrent Neural Networks), 33, 34
Rodríguez Vázquez, S., 181–182
Roelofsen, Floris, 159
Romania, sign language translation tools in, 158
Romanian Sign Language (LSR), 158
Rule-based machine translation
generally, 19
direct translation, 21
interlingua-based translation, 22
intermediate structures, 19–20
lexical disambiguation, 23
semantics in, 22–25
syntactic versus semantic features, 19–20
transfer-based translation, 21–22
Vauquois triangle, 20–21
RVMs. See Relevance vector machines (RVMs)
SantéBD, 131, 132
Schuurman, I., 131–133
Sclera, 131–133, 135–137, 142–143, 144
Sehda, Inc., 55, 56
SELECT, 59
Seligman, Mark, 61
Sevens, L., 135
SigLa platform, 163–164, 169, 170
SignLab, 158
Sign language
American Sign Language (ASL), 157, 178
Dutch Sign Language (NGT), 158
French Belgian Sign Language (LSFB), 164–166, 167
German Sign Language (DGS), 157–158
LSFB, 170
Romanian Sign Language (LSR), 158
Swiss-French Sign Language (LSF-CH) (See Swiss-French Sign Language (LSF-CH))
Swiss-German Sign Language (DSGS), 154–155
Swiss-Italian Sign Language (LIS-SI), 154–155
in Switzerland, 154–155
translation tools
generally, 157, 159
HospiSign, 158–159
Medical Signbank, 157
Pisourd, 157, 159
SignLab, 158
TraducMed, 157
World Health Sign, 157
Smartphones, 53
S-MINDS, 55–56, 71
SMOG Index, 89–93
SMOTE (Synthetic Minority Oversampling Technique), 104
SMT (Statistical machine translation), 25–28
SNOMED-CT, 71
Sofmax, 39
Spain, sign language translation tools in, 157
Speak & Translate, 53
Speech and language translation technologies
generally, 10–11, 40
abstract, 100
automatic speech recognition (ASR) (See automatic speech recognition (ASR))
healthcare applications (See Healthcare applications)
machine translation (MT) (See machine translation (MT))
text-to-speech (TTS) (See text-to-speech (TTS))
Speech synthesis. See text-to-speech (TTS)
Standard Rules on the Equalization of Opportunities for Persons with Disabilities, 156
Statistical machine translation (SMT), 25–28
Strategy for the Rights of Persons with Disabilities 2021–2030, 175
Support vector machines (SVMs), 93
SUS (System Usability Scale), 140
Sustainable Development Goals, 175
SVMs (Support vector machines), 93
Swiss-French Sign Language (LSF-CH)
generally, 7–8, 154–155, 169
abstract, 152
Deaf community and, 153, 154
development of, 159–160
Françoise avatar, 161
future research, 169–170
Gestural Signing Gesture Markup Language (G-SigML), 161–164
Hamburg Notation System for Sign Languages (HNS), 161
JASigning avatar, 158, 161–164
LiteDevTool, 169
qualitative evaluation of, 164–169
recording of translations
generally, 160
images, 160
medical jargon, 160
paraphrases, 160
proper names, 160
recording medium, 160
sample sentences, 161–
subtitles, 160
SigLa platform, 163–164, 169, 170
sign tables, 163
Speech2sign version, 164
virtual avatars, 161–164
Swiss-German Sign Language (DSGS), 154–155
Swiss-Italian Sign Language (LIS-SI), 154–155
Switzerland
Constitution, 156
Deaf community in
generally, 154
access to healthcare by, 153–154
legal framework, 154–155
sign language, 154–155
Disability Equality Act, 156
Federal Statistical Office, 152–153
language barriers in, 152–153
right to health in, 156
sign language translation tools in, 157
Swiss Federation of the Deaf, 155
Swiss-French Sign Language (LSF-CH) (See Swiss-French Sign Language (LSF-CH))
Synthetic Minority Oversampling Technique (SMOTE), 104
System Usability Scale (SUS), 140
SYSTRAN, 28–29, 31
Tablets, 53
TalkMondo, 53
Talk To Me, 72, 129
Text-to-speech (TTS)
generally, 13
concatenative TTS
generally, 13–14
allophones, 14
coarticulation, 14
extra-prosodic speech features, 15
lexical disambiguation, 14–15
normalization, 15
pronunciation problems, 15
prosody, 15
neural TTS
generally, 16
control points, absence of, 17
insufficient training data, 17
neural vocoders, 17
pronunciation problems, 17
prosody, 17
time and computation required, 17
TraducMed, 157
Transformers
generally, 32
attention across languages, 38–40
attention as context-worthiness, 33–35
context, role of, 32–33
Convolutional Neural Networks (CNNs), 35–36
delivery, 39–40
encoder layers, 36–38
as general purpose predictors, 35–36
Large Language Models (LLMs), 34, 35
Recurrent Neural Networks (RNNs), 33, 34
vanishing gradient problem, 33
Translational Web Corpus of Medical Spanish (TWCoMS), 180
Translation memory, 48–49
Translation samples, 45–46
Translation Shortcuts
generally, 7, 58, 59–60, 65
access to storage, 65
Browser, 66, 67
multimodal input, 60–61
Search, 66–67
verification of translations, 65
TTS. See text-to-speech (TTS)
Turkey, sign language translation tools in, 158–159
TWCoMS (Translational Web Corpus of Medical Spanish), 180
Uchida, Hiroshi, 24–25
UNCRPD (Convention on the Rights of Persons with Disabilities), 156
United Kingdom
British National Corpus, 103, 108
Deaf community, access to healthcare by, 153
Royal National Institute for Deaf People, 153
United Nations
Convention on the Rights of Persons with Disabilities (UNCRPD), 156
on people with disabilities (PwD), 175–176
Standard Rules on the Equalization of Opportunities for Persons with Disabilities, 156
Sustainable Development Goals, 175
World Programme of Action concerning Disabled Persons, 156
United States
Americans with Disabilities Act (ADA), 184
Bureau of Labor Statistics, 100–101
Deaf community, access to healthcare by, 153
Defense Advanced Research Programs Agency, 57–58
Department of Justice (DOJ), 184
Health Insurance Portability and Accountability Act (HIPAA), 54
localization of healthcare websites in, 179–180
multilingual healthcare website accessibility in, 181
National Library of Medicine (NLM), 183
Universal Declaration of Human Rights, 156
Universal Doctor, 72, 129, 154
Universal Networking Language (UNL), 24–25
University of Cambridge, 100
University of East Anglia, 161
University of Geneva, 1, 5–6, 56, 134, 144
University of Göttingen, 157–158
University of Lancaster, 84
University of Sydney, 1
University of Texas at Austin, 104
University of Tokyo, 68
UNL (Universal Networking Language), 24–25
USAS (Lancaster Semantic Annotation System), 84, 103
USP, 131
Valizadeh-Haghi, S., 177–178
Vandeghinste, V., 131–133
Vanishing gradient problem, 33
Vaschalde, C., 131–133
Vauquois triangle, 20–21
VCM (Visualisation of Concepts in Medicine), 131
ViSiCAST, 161
Visualisation of Concepts in Medicine (VCM), 131
Viterbi algorithms, 11
Waibel, Alex, 52, 56
WAI (Web Accessibility Initiative), 187
WaveNet, 17
Way, Andy, 118
WCAG. See Web Content Accessibility Guidelines (WCAG)
Wearables, 53
Web Accessibility Initiative (WAI), 187, 200
Web Content Accessibility Guidelines (WCAG), 177, 181, 184, 185–186, 197
WHO. See World Health Organisation (WHO)
Widgit Health, 131
Wołk, K., 134
Word Magic, 19, 23, 59
World Health Organization (WHO), 2–3, 154, 155–156
World Health Sign, 157
World Programme of Action concerning Disabled Persons, 156
World Wide Web Consortium (W3C), 177, 199
W3C (World Wide Web Consortium), 177, 199
Yi, Y.J., 178
Youngblood, N.E., 178
Yu, B., 133
Yunker, J., 202
Zeng, X., 177
Zeng-Treitler, Q., 131
“Zero-shot” NMT, 31
Zoom, 52

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  • Index
  • Meng Ji, University of Sydney, Pierrette Bouillon, Université de Genève, Mark Seligman, Spoken Translation Technology
  • Book: Translation Technology in Accessible Health Communication
  • Online publication: 31 August 2023
  • Chapter DOI: https://doi.org/10.1017/9781108938976.009
Available formats
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  • Index
  • Meng Ji, University of Sydney, Pierrette Bouillon, Université de Genève, Mark Seligman, Spoken Translation Technology
  • Book: Translation Technology in Accessible Health Communication
  • Online publication: 31 August 2023
  • Chapter DOI: https://doi.org/10.1017/9781108938976.009
Available formats
×

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To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Index
  • Meng Ji, University of Sydney, Pierrette Bouillon, Université de Genève, Mark Seligman, Spoken Translation Technology
  • Book: Translation Technology in Accessible Health Communication
  • Online publication: 31 August 2023
  • Chapter DOI: https://doi.org/10.1017/9781108938976.009
Available formats
×