December 11-16 2016 Osaka Japan

More documents

Recommendations

Info

Figure 10: Official evaluation results of JPC-KJ. 22
Figure <strong>11</strong>: Official evaluation results of BPPT-IE. 23
Page 1 and 2: WAT 2016 The 3rd Workshop on Asian
Page 3: Preface Many Asian countries are ra
Page 6 and 7: Technical Collaborators Luis Fernan
Page 9 and 10: Table of Contents Overview of the 3
Page 11 and 12: Conference Program December 12, 201
Page 13 and 14: December 12, 2016 (continued) 12:00
Page 15 and 16: Overview of the 3rd Workshop on Asi
Page 17 and 18: LangPair Train Dev DevTest Test JPC
Page 19 and 20: ASPEC JPC IITB BPPT pivot System ID
Page 21 and 22: 3.6 Tree-to-String Syntax-based SMT
Page 23 and 24: • Use of other resources in addit
Page 25 and 26: ASPEC JPC BPPT IITBC pivot Team ID
Page 27 and 28: ut the adequacy is worse. As for AS
Page 29 and 30: Figure 3: Official evaluation resul
Page 35: Figure 9: Official evaluation resul
Page 39 and 40: Figure 13: Official evaluation resu
Page 41 and 42: Annotator A Annotator B all weighte
Page 43 and 44: Kyoto-U 2 bjtu nlp UT-KAY 1 UT-KAY
Page 45 and 46: Online B IITP-MT EHR Online A ≫
Page 47 and 48: SYSTEM ID ID METHOD OTHER RESOURCES
Page 49 and 50: SYSTEM ID ID METHOD OTHER BLEU RIBE
Page 59 and 60: Hyoung-Gyu Lee, JaeSong Lee, Jun-Se
Page 61 and 62: Translation of Patent Sentences wit
Page 63 and 64: Chinese sentences contain fewer tha
Page 65 and 66: Figure 3: NMT decoding with technic
Page 67 and 68: Table 1: Automatic evaluation resul
Page 69 and 70: Figure 6: Example of correct transl
Page 71 and 72: K. Papineni, S. Roukos, T. Ward, an
Page 73 and 74: Table 1: Examples of title, ingredi
Page 75 and 76: text. In this section, we explain t
Page 77 and 78: Table 3: Automatic evaluation BLEU/
Page 79 and 80: Table 5: Number of fluency errors i
Page 81 and 82: Kenneth Heafield. 2011. Kenlm: Fast
Page 83 and 84: under-studied. MorphInd, a morphana
Page 85 and 86: dimensions of 150 units in second h
Page 87 and 88:
distribution as received in JPO ade
Page 89 and 90:
Domain Adaptation and Attention-Bas
Page 91 and 92:
Once s M , which represents the ent
Page 93 and 94:
3.4.2 Ensemble of Attention Scores
Page 95 and 96:
Type Count Ratio (A) Correct 76 30.
Page 97 and 98:
Minh-Thang Luong, Hieu Pham, and Ch
Page 99 and 100:
Pair 1 Japanese [[ A ][ B ][ C ]
Page 101 and 102:
ID n-grams len freq m1 prevent, | 1
Page 103 and 104:
prediction accuracy with respect to
Page 105 and 106:
Reference: [ A To provide] [ B a to
Page 107 and 108:
Philipp Koehn. 2004. Statistical si
Page 109 and 110:
Therefore, we propose to use phrase
Page 111 and 112:
Figure 2: An NRM considering phrase
Page 113 and 114:
Mono Swap D right D left Acc. The r
Page 115 and 116:
Method ja-en en-ja BLEU RIBES WER B
Page 117 and 118:
Peng Li, Yang Liu, and Maosong Sun.
Page 119 and 120:
Figure 1: The framework of NMT. Whe
Page 121 and 122:
For long sentence, we discarded all
Page 123 and 124:
As shown in the above tables and fi
Page 125 and 126:
Translation systems and experimenta
Page 127 and 128:
The number of TM training sentence
Page 129 and 130:
where, f, p and e means a source, p
Page 131 and 132:
former system can translate more th
Page 133 and 134:
Lexicons and Minimum Risk Training
Page 135 and 136:
2.2 Parameter Optimization If we de
Page 137 and 138:
ML (λ=0.0) ML (λ=0.8) MR (λ=0.0)
Page 139 and 140:
Graham Neubig. 2013. Travatar: A fo
Page 141 and 142:
Feature Space Common (h ) Domain 1
Page 143 and 144:
Preprocessing Training Translation
Page 145 and 146:
JPC ASPEC LM Method Ja-En En-Ja Ja-
Page 147 and 148:
Translation Using JAPIO Patent Corp
Page 149 and 150:
4 Results Table 1 shows official ev
Page 151 and 152:
Table 3: Examples of translation er
Page 153 and 154:
An Efficient and Effective Online S
Page 155 and 156:
#$ #%$ #$ !""
Page 157 and 158:
This formula requires a context of
Page 159 and 160:
Sentence Segmenter Parameters Dev.
Page 161 and 162:
a meaningful baseline for related r
Page 163 and 164:
Similar Southeast Asian Languages:
Page 165 and 166:
τ around 0.71, and the Malay-Indon
Page 167 and 168:
-0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3
Page 169 and 170:
1.800 1.600 1.400 1.200 1.000 0.800
Page 171 and 172:
Integrating empty category detectio
Page 173 and 174:
3 Preordering with empty categories
Page 175 and 176:
We performed the tests under two co
Page 177 and 178:
the decoded sentence and the refere
Page 179 and 180:
Kenneth Heafield. 2011. Kenlm: Fast
Page 181 and 182:
Figure 1: Overview of KyotoEBMT. Th
Page 183 and 184:
proportionally slower to compute (a
Page 185 and 186:
3.6 Ensembling Ensembling has previ
Page 187 and 188:
when Chinese is also the language m
Page 189 and 190:
Character-based Decoding in Tree-to
Page 191 and 192:
where W s ∈ R d×d is a matrix an
Page 193 and 194:
Model BLEU (BP) RIBES Character-bas
Page 195 and 196:
The word-based NMT models cannot us
Page 197 and 198:
Razvan Pascanu, Tomas Mikolov, and
Page 199 and 200:
governs the grammaticality of the t
Page 201 and 202:
2.1 Quantization and Binarization o
Page 203 and 204:
3 Results Team Other Resources Syst
Page 205 and 206:
Peter F Brown, John Cocke, Stephen
Page 207 and 208:
Yonghui Wu, Mike Schuster, Zhifeng
Page 209 and 210:
Language Sentence Chinese 该 / 钽
Page 211 and 212:
Chinese or Japanese sentences Chine
Page 213 and 214:
4 Experiments and Results 4.1 Chine
Page 215 and 216:
6 Conclusion and Future Work In thi
Page 217 and 218:
Controlling the Voice of a Sentence
Page 219 and 220:
Figure 2: Flow of the voice predict
Page 221 and 222:
ecause the number of passive senten
Page 223 and 224:
controlling the sentence length wit
Page 225 and 226:
Chinese-to-Japanese Patent Machine
Page 227 and 228:
using the reordering oracles over t
Page 229 and 230:
Conference on Natural Language Proc
Page 231 and 232:
Figure 1: Hierarchical approach wit
Page 233 and 234:
newswire test and development set o
Page 235 and 236:
Source: the rain and cold wind on W
Page 237 and 238:
Residual Stacking of RNNs for Neura
Page 239 and 240:
2.2 Generalized Minimum Bayes Risk
Page 241 and 242:
5.0 4.5 4.0 Baseline model Enlarged
Page 243:
Felix Hill, Kyunghyun Cho, Sebastie
show all

December 11-16 2016 Osaka Japan

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?