By Takako Aikawa, Kentaro Yamamoto, Hitoshi Isahara (auth.), Hitoshi Isahara, Kyoko Kanzaki (eds.)
This booklet constitutes the refereed complaints of the eighth foreign convention on Advances in typical Language Processing, JapTAL 2012, Kanazawa, Japan, in October 2012.
The 27 revised complete papers and five revised brief papers offered have been conscientiously reviewed and chosen from forty two submissions. The papers are prepared in topical sections on computer translation, multilingual concerns, resouces, semantic research, sentiment research, in addition to speech and generation.
Read or Download Advances in Natural Language Processing: 8th International Conference on NLP, JapTAL 2012, Kanazawa, Japan, October 22-24, 2012. Proceedings PDF
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Additional resources for Advances in Natural Language Processing: 8th International Conference on NLP, JapTAL 2012, Kanazawa, Japan, October 22-24, 2012. Proceedings
Each step in the system can introduce a certain number of errors. It is important to highlight the feasibility of the approach and the impact of each module on the generated data. Thus, we conducted three diﬀerent types of experiments, described in Figure 2. In the ﬁrst experiment (Exp 1 ) we use the reference translations as queries for the IR system. This is Exp 1 Exp 2 Exp 3 TED audio ASR TEDbi. En SMT TEDbi. FR TEDbi_tran. FR TEDasr. En SMT TEDasr_tran . fr Fig. 2. Diﬀerent experiments to analyze the impact of the errors of each module 44 H.
Murakami Fig. 7. Selection from translation candidates 5 Experiments First, we carried out the closed-test to check the implementation of ITM-p. Next, we carried out the open-test to investigate eﬀectiveness of the proposed method. 1 Closed-Test Experimental Method. To survey our system, the closed-test was carried out with input sentences from the Japanese-English compound and complex sentence pattern dictionary. We used 500 input sentences for pattern matching and selected 100 sentences to evaluate translation accuracy.
Table 3 shows the evaluation results. Table 3. 3 27 68 5 Fig. 9 shows examples of Eval. 1 and Eval. 2. All results in Eval. 3 are caused by wrong sentence pattern description. In Eval. 1, the sentence structure and all local translations are correct. In Eval. 2, sentence structure is correct, but local translations of NP1 and N3 are not correct. 1> Input Sentence: Reference Sentence: English Pattern: Matched Morphemes: Output Sentence: γϬϲ䈽ϳχ⑳Ϋζϫϲᜧό [Kore wo yon de naka zaru wo e nu] I can not read this without crying.
Advances in Natural Language Processing: 8th International Conference on NLP, JapTAL 2012, Kanazawa, Japan, October 22-24, 2012. Proceedings by Takako Aikawa, Kentaro Yamamoto, Hitoshi Isahara (auth.), Hitoshi Isahara, Kyoko Kanzaki (eds.)