A Machine Learning Approach to Evaluating Translation Quality
- Reyes Ayala, Brenda
- Chen, Jiangping
Publication date
June 2017
DOIAbstract
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
In this paper we introduce MoBiL, a hybrid Monolingual, Bilingual and Language modelling feature set...
We introduce the Machine Translation (MT) evaluation survey that contains both manual and automatic ...
We report on various approaches to automatic evaluation of machine translation quality and describe ...
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
In the context of an increasingly networked world, the availability of high quality translations is ...
In the context of an increasingly networked world, the availability of high quality translations is ...
The problem of evaluating machine translation (MT) systems is more challenging than it may first app...
Any scientific endeavour must be evaluated in order to assess its correctness. In many applied scien...
This work was supported by the Spanish Ministry of Science, Innovation and Universities (MCIU) (RTI...
Discriminative training, a.k.a. tuning, is an important part of Statistical Machine Translation. Thi...
Assessing Machine Translation (MT) quality at document level is a challenge as metrics need to accou...
We introduce the Machine Translation (MT) evaluation survey that contains both manual and automatic ...
Most evaluation metrics for machine translation (MT) require reference translations for each sentenc...
Translations generated by current statistical systems often have a large variance, in terms of their...
In this paper we introduce MoBiL, a hybrid Monolingual, Bilingual and Language modelling feature set...
We introduce the Machine Translation (MT) evaluation survey that contains both manual and automatic ...
We report on various approaches to automatic evaluation of machine translation quality and describe ...
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
This paper explores the possibility of applying Machine Learning for Machine Translation evaluation
In the context of an increasingly networked world, the availability of high quality translations is ...
In the context of an increasingly networked world, the availability of high quality translations is ...
The problem of evaluating machine translation (MT) systems is more challenging than it may first app...
Any scientific endeavour must be evaluated in order to assess its correctness. In many applied scien...
This work was supported by the Spanish Ministry of Science, Innovation and Universities (MCIU) (RTI...
Discriminative training, a.k.a. tuning, is an important part of Statistical Machine Translation. Thi...
Assessing Machine Translation (MT) quality at document level is a challenge as metrics need to accou...
We introduce the Machine Translation (MT) evaluation survey that contains both manual and automatic ...
Most evaluation metrics for machine translation (MT) require reference translations for each sentenc...
Translations generated by current statistical systems often have a large variance, in terms of their...
In this paper we introduce MoBiL, a hybrid Monolingual, Bilingual and Language modelling feature set...
We introduce the Machine Translation (MT) evaluation survey that contains both manual and automatic ...
We report on various approaches to automatic evaluation of machine translation quality and describe ...
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