Related papers: Noun Phrase Reference in Japanese-to-English Machi…
This paper presents a heuristic method that uses information in the Japanese text along with knowledge of English countability and number stored in transfer dictionaries to determine the countability and number of English noun phrases.…
The referential properties of noun phrases in the Japanese language, which has no articles, are useful for article generation in Japanese-English machine translation and for anaphora resolution in Japanese noun phrases. They are generally…
When translating Japanese nouns into English, we face the problem of articles and numbers which the Japanese language does not have, but which are necessary for the English composition. To solve this difficult problem we classified the…
Possessive pronouns are used as determiners in English when no equivalent would be used in a Japanese sentence with the same meaning. This paper proposes a heuristic method of generating such possessive pronouns even when there is no…
In machine translation and man-machine dialogue, it is important to clarify referents of noun phrases. We present a method for determining the referents of noun phrases in Japanese sentences by using the referential properties, modifiers,…
This paper proposes an analysis of classifiers into four major types: UNIT, METRIC, GROUP and SPECIES, based on properties of both Japanese and English. The analysis makes possible a uniform and straightforward treatment of noun phrases…
This paper describes in outline a method for translating Japanese temporal expressions into English. We argue that temporal expressions form a special subset of language that is best handled as a special module in machine translation. The…
We have developed a new method for Japanese-to-English translation of tense, aspect, and modality that uses an example-based method. In this method the similarity between input and example sentences is defined as the degree of semantic…
Recently, several types of Japanese-to-English machine translation systems have been developed, but all of them require an initial process of rewriting the original text into easily translatable Japanese. Therefore these systems are…
Pronouns are important determinants of a text's meaning but difficult to translate. This is because pronoun choice can depend on entities described in previous sentences, and in some languages pronouns may be dropped when the referent is…
It is challenging to translate names and technical terms across languages with different alphabets and sound inventories. These items are commonly transliterated, i.e., replaced with approximate phonetic equivalents. For example, "computer"…
Most state-of-the-art neural machine translation systems, despite being different in architectural skeletons (e.g. recurrence, convolutional), share an indispensable feature: the Attention. However, most existing attention methods are…
Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT). Despite its recent success, NMT cannot…
The performance of machine learning algorithms can be improved by combining the output of different systems. In this paper we apply this idea to the recognition of noun phrases.We generate different classifiers by using different…
We compare three approaches to statistical machine translation (pure phrase-based, factored phrase-based and neural) by performing a fine-grained manual evaluation via error annotation of the systems' outputs. The error types in our…
For Japanese-to-English translation, zero pronouns in Japanese pose a challenge, since the model needs to infer and produce the corresponding pronoun in the target side of the English sentence. However, although fully resolving zero…
Machine translation is the process of translating text from one language to another. In this paper, Statistical Machine Translation is done on Assamese and English language by taking their respective parallel corpus. A statistical phrase…
Phrases play an important role in natural language understanding and machine translation (Sag et al., 2002; Villavicencio et al., 2005). However, it is difficult to integrate them into current neural machine translation (NMT) which reads…
In this paper, we introduce a hybrid search for attention-based neural machine translation (NMT). A target phrase learned with statistical MT models extends a hypothesis in the NMT beam search when the attention of the NMT model focuses on…
We consider phrase based Language Models (LM), which generalize the commonly used word level models. Similar concept on phrase based LMs appears in speech recognition, which is rather specialized and thus less suitable for machine…