3. Grammatical Error Correction (GEC) 3
Ungrammatical
sentence
Grammatical
& Fluent
sentence
o Rule based model
o Classifiers
o Phrase-based MT
o Neural MT
4. Grammatical Error Correction (GEC) 4
Ungrammatical
sentence
Grammatical
& Fluent
sentence
o Rule based model
o Classifiers
o Phrase-based MT
o Neural MT
5. Neural MT for GEC (Encoder-decoder with attention) 5
x2 xS-1 xSx1
Encoder
6. Neural MT for GEC (Encoder-decoder with attention) 6
x2 xS-1 xSx1
NULL
y1
Encoder
Decoder
7. Neural MT for GEC (Encoder-decoder with attention) 7
x2 xS-1 xSx1
+
NULL
y1 y2
Encoder
Decoder
8. Neural MT for GEC (Encoder-decoder with attention) 8
x2 xS-1 xSx1
+
NULL
y1 y2 yT-1 yT
Encoder
Decoder
9. Neural MT for GEC (Encoder-decoder with attention) 9
Training objective: Maximum Likelihood Estimation
log $(&')
log $(&)*+)
log $(&))
gold label
log $(&+)
NULL
Decoder
10. Two Drawbacks in MLE 10
#1 Word level optimization (not sentence-level)
log $(&')
log $(&)*+)
log $(&))
gold label
log $(&+)
NULL
Decoder
11. Two Drawbacks in MLE 11
#2 Exposure Bias (gold in training, argmax in test)
gold label
NULL
Predicted word (might be erroneous) is fed during test time.
y’1 = y1
y’2
y2
y’T-1
yT-1
yT
y’T
Decoder
15. REINFORCE (Williams, 1992) 15
Maximize the expected reward (metric score)
Learning Rate
Relevance to Minimum Risk Training in NMT:
Learning rate ! in REINFORCE corresponds to
the smoothing parameter in MRT.
See the appendix.
16. GLEU (Napoles et al., 2015) 16
Penalize n-grams that match
between source and hypothesis
but not in reference
17. Experiment 17
Data:
Training: Cambridge Learner Corpus (FCE)
NUCLE Corpus
Lang8 Corpus
Dev & Test: JFLEG Corpus
Model (hyper-)parameters:
Embedding: 512, Hidden: 1000, Dropout: 0.2,
(for NRL)
Sample size: 20, warm start: after 600k updates in MLE
Metric (= score, reward):
GLEU
23. Summary 23
Grammatical Error Correction with NRL
ü Sentence-level objective.
ü Direct optimization toward the metric.
ü NRL > Maximum Likelihood Estimation
24. Example Outputs 24
SRC Fish firming uses the lots of special products such as fish meal .
REF Fish firming uses a lot of special products such as fish meal .
PBMT Fish firming uses a lot of special products such as fish meal .
MLE Fish contains a lot of special products such as fish meals .
NRL Fish shops use lots of special products such as fish meal .
SRC but found that successful people use the people money and use there
idea for a way to success .
REF But it was found that successful people use other people 's money and
use their ideas as a way to success .
PBMT but found that successful people use the money and use these ideas for
a way to success .
MLE But found that successful people use the people money and use it for a
way to success .
NRL But found that successful people use the people 's money and use their
idea for a way to success .
