A Natural Language Sentence Analysis Algorithm Based on Word Order Modifier Syntax Rules

Jia, Ji Kang; Shao, Yu Bin; Long, Hua; Du, Qing

doi:10.1016/j.procs.2020.02.058

Cited by 3 publications

(1 citation statement)

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“…In the process of the development of information retrieval, people put forward various retrieval models, which have been widely applied at present; there are Boolean model and vector space model [3]. ere are many variations according to these models, such as extended Boolean model [4], generalized vector model [5], latent semantic indexing model, and neural network model.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] English Audio Language Retrieval Based on Adaptive Speech‐Adjusting Algorithm

Feng

Zhou

2021

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For the purpose of language retrieval for English listening, this paper designs and implements a cross-language information retrieval system for English listening. Different implementation methods of cross-language information retrieval, query, and translation are analyzed. The system adopts cross-language information retrieval technology based on bilingual dictionaries. According to the cross-language retrieval system of the existing bilingual dictionaries and monolingual dictionaries, based on the design and implementation of the fuzzy search dictionary lookup mechanism, the existing dictionary lookup mechanism is constructed and analyzed. Aiming at the problem of translation ambiguity in information retrieval systems based on bilingual dictionaries, a disambiguities elimination algorithm based on cooccurrence technology is proposed. In continuous speech, the speed of different speakers in different contexts is very different. Deviation from normal speech speed often leads to recognition errors, which makes recognition performance decline. Considering that the influence of speech speed on the length of speech units increases or decreases synchronously, and there is a strong correlation between the lengths of adjacent speech units, an adaptive speech speed algorithm is proposed based on the framework of implicit Markov model based on the information of the length of speech units. Experiments on number string and large vocabulary continuous speech recognition show that the algorithm is effective.

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Section: Introductionmentioning

confidence: 99%