A mathematical model that makes use of data mining and soft computing techniques is proposed to estimate the software development effort. The proposed model works as follows: The parameters that have impact on the dev...A mathematical model that makes use of data mining and soft computing techniques is proposed to estimate the software development effort. The proposed model works as follows: The parameters that have impact on the development effort are divided into groups based on the distribution of their values in the available dataset. The linguistic terms are identified for the divided groups using fuzzy functions, and the parameters are fuzzified. The fuzzified parameters then adopt associative classification for generating association rules. The association rules depict the parameters influencing the software development effort. As the number of parameters that influence the effort is more, a large number of rules get generated and can reduce the complexity, the generated rules are filtered with respect to the metrics, support and confidence, which measures the strength of the rule. Genetic algorithm is then employed for selecting set of rules with high quality to improve the accuracy of the model. The datasets such as Nasa93, Cocomo81, Desharnais, Maxwell, and Finnish-v2 are used for evaluating the proposed model, and various evaluation metrics such as Mean Magnitude of Relative Error, Mean Absolute Residuals, Shepperd and MacDonell’s Standardized Accuracy, Enhanced Standardized Accuracy and Effect Size are adopted to substantiate the effectiveness of the proposed methods. The results infer that the accuracy of the model is influenced by the metrics support, confidence, and the number of association rules considered for effort prediction.展开更多
The main objective of this paper is to convert the written multilingual text into machine generated synthetic speech. This paper is proposed in order to provide a complete multilingual speech synthesizer for three lan...The main objective of this paper is to convert the written multilingual text into machine generated synthetic speech. This paper is proposed in order to provide a complete multilingual speech synthesizer for three languages Indian English, Tamil and Telugu. The main application of TTS system is that it will be helpful for blind and mute people that they could have the text read to them by computer. TTS system will help in retrieving the information from sites that contain information in different languages. It can be used in educational institutions for pronunciation teaching of different languages. We use concatenative speech syn-thesis where the segments of recorded speech are concatenated to produce the desired output. We apply prosody which makes the synthesized speech sound more like human speech. Smoothing is also done to smooth the transition between segments in order to produce continuous output. The Optimal Coupling algorithm is enhanced to improve the performance of speech synthesis system.展开更多
文摘A mathematical model that makes use of data mining and soft computing techniques is proposed to estimate the software development effort. The proposed model works as follows: The parameters that have impact on the development effort are divided into groups based on the distribution of their values in the available dataset. The linguistic terms are identified for the divided groups using fuzzy functions, and the parameters are fuzzified. The fuzzified parameters then adopt associative classification for generating association rules. The association rules depict the parameters influencing the software development effort. As the number of parameters that influence the effort is more, a large number of rules get generated and can reduce the complexity, the generated rules are filtered with respect to the metrics, support and confidence, which measures the strength of the rule. Genetic algorithm is then employed for selecting set of rules with high quality to improve the accuracy of the model. The datasets such as Nasa93, Cocomo81, Desharnais, Maxwell, and Finnish-v2 are used for evaluating the proposed model, and various evaluation metrics such as Mean Magnitude of Relative Error, Mean Absolute Residuals, Shepperd and MacDonell’s Standardized Accuracy, Enhanced Standardized Accuracy and Effect Size are adopted to substantiate the effectiveness of the proposed methods. The results infer that the accuracy of the model is influenced by the metrics support, confidence, and the number of association rules considered for effort prediction.
文摘The main objective of this paper is to convert the written multilingual text into machine generated synthetic speech. This paper is proposed in order to provide a complete multilingual speech synthesizer for three languages Indian English, Tamil and Telugu. The main application of TTS system is that it will be helpful for blind and mute people that they could have the text read to them by computer. TTS system will help in retrieving the information from sites that contain information in different languages. It can be used in educational institutions for pronunciation teaching of different languages. We use concatenative speech syn-thesis where the segments of recorded speech are concatenated to produce the desired output. We apply prosody which makes the synthesized speech sound more like human speech. Smoothing is also done to smooth the transition between segments in order to produce continuous output. The Optimal Coupling algorithm is enhanced to improve the performance of speech synthesis system.
