The argument related to the use of real and anonymous names on the Internet bulletin board has recently become a main issue. When using real names, it is possible to violate free discussion and privacy. Also, when using anonymous names, it is possible to have the reverse function of the Internet in regard to the use of malicious replies or the distribution of false ideas. Therefore, this paper has made it possible to prevent the spread of the user's personal information and execute the single log-in process by using the XML-token method which is one of the SSO technologies. Also, by issuing virtual IDs and forming the path when establishing tokens, the anonymous bulletin board which provides anonymity with a conditional tracing process has been suggested. After analyzing the performance of visitor numbers at authentication time, the anonymous bulletin board based on the group signature method showed the average response rate of 0.72 seconds, 0.18 seconds, which was suggested scheme. In the authentication time 4-5 times faster response speed, respectively. Also, since the suggested system does not have to provide a single authentication process or make the user provide his or her signature, the level of user's convenience seems to be much higher. Such a result shows that the system suggested on the anonymous bulletin board has a more appropriate level of user's convenience.
This paper is related to the method of adding a emotional speech corpus to a high-quality large corpus based speech synthesizer, and generating various synthesized speech. We made the emotional speech corpus as a form which can be used in waveform concatenated speech synthesizer, and have implemented the speech synthesizer that can be generated various synthesized speech through the same synthetic unit selection process of normal speech synthesizer. We used a markup language for emotional input text. Emotional speech is generated when the input text is matched as much as the length of intonation phrase in emotional speech corpus, but in the other case normal speech is generated. The BIs(Break Index) of emotional speech is more irregular than normal speech. Therefore, it becomes difficult to use the BIs generated in a synthesizer as it is. In order to solve this problem we applied the Variable Break[3] modeling. We used the Japanese speech synthesizer for experiment. As a result we obtained the natural emotional synthesized speech using the break prediction module for normal speech synthesize.
The exact fundamental frequency (pitch) extraction is important in speech signal processing. However the exact pitch extraction from speech signal is very difficult due to the effect of formant and transitional amplitude. So in this paper, the pitch is detected after flattening the spectrum in frequency region by proposed algorithm for minimized harmonics variance value. Experimental result showed the proposed method appeared an outstanding performance in compared with LPC, Cepstrum. Also, the results show the proposed method is better than conventional method.
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