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To solve the problems of tedious key-press and poor interaction in current agricultural information voice service system, a method based on keywords recognition for agricultural information voice service system is proposed in this paper. It simplifies inquiry process and enhances interaction with customers by
Most approaches towards automatic evaluation of free text answers are keyword centric. Though keywords essentially reflect and represent the primary concept coverage of an answer, they are incomplete without the associated texts. The words occurring before and after the keywords bring out the true meaning. The work
accuracy, measured energy, delay, and area in order to determine the best classes of approximation for low-energy and high-accuracy operation. A system-level evaluation of these methods was performed using a software model of a keyword detection speech pipeline to predict the impact of inaccurate logarithmic approximation on
English-Chinese translation system-YanFa-5 which integrates keyword matching scoring, sentence pattern matching scoring with semantic scoring. Experiment results show that YanFa-5 is more accurate in the assessment of student on-line English-Chinese translations.
context information and semantic similarity together. We searched a series of context structures for keywords in a sentence. Experiment has been carried out to show the effectiveness of our method.
(n=1, 766), and Secretary Albright from 1997-2001 (n=1, 335). We use computer-assisted content analysis to find key themes for each Secretary and search for similarities between key themes and phrases. We find a limited number of similar keywords across the dataset, except International and Issues. However, the
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