Part of
Translation in Transition: Human and machine intelligenceEdited by Isabel Lacruz
[American Translators Association Scholarly Monograph Series XX] 2023
► pp. 287–287
Edited by Isabel Lacruz
[American Translators Association Scholarly Monograph Series XX] 2023
► pp. 287–287
Index
A
- ambiguity, translation 8, 184–99
B
- big data 2, 6–7, 105, 109
- boundary condition 24, 27–29
C
- complexity theory 15, 19
- computationalism 262, 269, 275, 277
- CRITT TPR-DB 9–10, 203, 210, 243
- crowd-sourcing88
D
- discourse marker 132, 138, 143
E
- ear-pen span 7, 158, 166
- effort, cognitive 4, 11, 49, 51–52, 58–61, 64–65, 67–69, 71–72, 74, 243–44, 261, 263, 266
- emergence 3, 17–20, 22, 24, 26, 133
- enactivism. 267, 275
- evaluation, end-user100
- evaluation, human 5, 86–87, 90–98, 100
- eye-tracking 59, 108, 204
F
- Fortress Besieged 5, 105, 109–10, 113, 116–17, 119–21, 124–26
I
- Intelligence, Machine 2–3, 13
- interjection 132, 138, 141–43, 146, 148, 151
K
- keystroke 4, 9, 60, 77, 203–4, 243, 246, 261, 263, 270
M
- machine translation, neural 2–3, 39, 44, 51, 84
- metaphor 5–6, 105–6, 109–10, 112, 114–21, 123–27, 223–24, 269, 284
- Monitor Model 11–12, 242–43, 260, 262–63, 266–69, 271–77
N
- non-professional 6, 97–98, 130, 132–33
- note-taking 7, 157–63, 165–69, 174–77
- note-taking duration 162, 167
- note-taking unit 7, 158, 165
P
- parity, human-machine 5, 9, 83–85, 91, 93, 98
- participant profiling98
- phase space 29–30, 33–35
- post-editing 1, 3–5, 7, 9–11, 39–44, 47, 49, 51, 57–63, 66–71, 74–78, 87, 208, 210, 215, 244, 246, 249–52, 261
- processing, horizontal 10–12, 240–44, 248–49, 251, 263, 265, 271–72
- processing,vertical 1, 10–12, 240–43, 251, 262, 264
- proficiency, second language 9, 26, 183, 187–88, 190, 196–98, 238, 239
- Python 111, 118, 120, 126
S
- schema, annotation 7, 158, 163, 177
- sentiment analysis 105, 111–12
- strange attractor 3, 19, 24, 30–31
- subtitle length 6, 131, 137, 140, 151
- subtitling 108, 131–35, 137–38, 141, 151–52
- sustainable 4, 47, 53
- system, complex adaptive 16, 18–19, 21, 24–25, 30, 33, 36–37
T
- TED 130–40, 143, 146, 148, 151–52
- translation ambiguity 8–9, 183–84, 187–91, 193–95, 197–99
- translation competence 16, 19, 28, 40, 51–53
- translation entropy 10, 199, 204–6, 215, 217, 226, 229–31, 244, 248, 251–52
- translation expertise 16, 19, 21, 24, 36
- translation pedagogy 16, 22, 24, 27, 33, 36
- translation process research 3, 10, 13, 40, 49, 74, 203, 205, 236, 238, 245, 252, 257–58, 261
- translation reception 106, 108–9, 127
- translation, default 10, 31, 33, 238, 261, 272, 275
- translation, dominant 188, 194–97
- translation, human 1–4, 7–8, 39, 41–42, 58–61, 68–69, 77–78, 84–88, 96, 100, 208, 231, 275
- translation, literary 106, 108
- translation, machine 1–3, 5–8, 12, 26, 36, 39–40, 44, 47, 50–51, 57–62, 66–69, 71–72, 84, 131, 134, 152, 199, 208, 231, 249–52
V
- volunteer 6, 93, 130–5
W
- Weicheng 5, 105–6, 109–10, 114–16, 124–25
- word alignment 8, 204–6, 208–11, 213, 223, 225–31, 244
- word alignment, automatic206
- word translation entropy 10–11, 199, 204, 226, 230, 244, 247–48, 251, 252
