• Phonetics and Speech Sciences
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• v.9 no.1
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• pp.41-47
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• 2017

The main advantage of the statistical parametric speech synthesis is its flexibility in changing voice characteristics. A personalized text-to-speech(TTS) system can be implemented by combining a speech synthesis system and a voice transformation system, and it is widely used in many application areas. It is known that the fundamental frequency and the spectral envelope of speech signal can be independently modified to convert the voice characteristics. Also it is important to maintain naturalness of the transformed speech. In this paper, a speech synthesis system based on Hidden Markov Model(HMM-based speech synthesis, HTS) using the STRAIGHT vocoder is constructed and voice transformation is conducted by modifying the fundamental frequency and spectral envelope. The fundamental frequency is transformed in a scaling method, and the spectral envelope is transformed through frequency warping method to control the speaker's vocal tract length. In particular, this study proposes a voice transformation method using the correlation between fundamental frequency and vocal tract length. Subjective evaluations were conducted to assess preference and mean opinion scores(MOS) for naturalness of synthetic speech. Experimental results showed that the proposed voice transformation method achieved higher preference than baseline systems while maintaining the naturalness of the speech quality.

• Speech Sciences
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• v.2
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• pp.25-44
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• 1997

When listening the various speech synthesis systems developed and being used in our country, we find that though the quality of these systems has improved, they lack naturalness. Moreover, since the voice color of these systems are limited to only one recorded speech DB, it is necessary to record another speech DB to create different voice colors. 'Voice Color' is an abstract concept that characterizes voice personality. So speech synthesis systems need a voice color control function to create various voices. The aim of this study is to examine several factors of voice color control rules for the text-to-speech system which makes natural and various voice types for the sounding of synthetic speech. In order to find such rules from natural speech, glottal source parameters and frequency characteristics of the vocal tract for several voice colors have been studied. In this paper voice colors were catalogued as: deep, sonorous, thick, soft, harsh, high tone, shrill, and weak. For the voice source model, the LF-model was used and for the frequency characteristics of vocal tract, the formant frequencies, bandwidths, and amplitudes were used. These acoustic parameters were tested through multiple regression analysis to achieve the general relation between these parameters and voice colors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.713-725
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• 2022

Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.12 no.2
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• pp.115-120
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• 2001

In this paper, we synthesized vowel /ae/ with voice synthesis program of Dr. Speech Science, and we also synthesized pathologic vowel /ae/ by some parameters such as high frequency gain (HFG), low frequency gain(LFG), pitch flutter(PF) which represents jitter value and flutter of amplitude(FA) which represents shimmer value, and grade ranked as mild, moderate and severe respectively. And then we analysed all pathologic voice by analysis program of Dr. Speech Science. We expect that this synthesized pathologic voices are useful for understanding the parameter such as noise, jitter and shimmer and feedback effect to patient with voice disorder.

• Journal of Digital Contents Society
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• v.11 no.2
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• pp.235-242
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• 2010

Differently from instruments which synthesized sounds and tones in the past, voice synthesis engine for music production has reached to the level of creating music as if actual artists were singing. It uses the samples of human voices naturally connected to the different levels of phoneme within the frequency range. Voice synthesis engine is not simply limited to the music production but it is changing cultural paradigm through the second creations of new music type including character music concerts, media productions, albums, and mobile services. Currently, voice synthesis engine technology makes it possible that users input pitch, lyrics, and musical expression parameters through the score editor and they mix and connect voice samples brought from the database to sing. New music types derived from such a development of computer music has sparked a big impact culturally. Accordingly, this paper attempts to examine the specific case studies and the synthesis technologies for users to understand the voice synthesis engine more easily, and it will contribute to their variety of music production.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.57-66
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• 2006

In this paper, I propose a new method of Multi-Pulse Speech Coding(FBD-MPC: Frequency Band Division MPC) by using TSIUVC(Transition Segment Including UnVoiced Consonant) searching, extraction and approximation-synthesis method in a frequency domain. As, a result. the extraction rates of TSIUVC are 84.8%(plosive), 94.9%(fricative) and 92.3%(affricative) in female voice, 88%(plosive), 94.9%(fricative) and 92.3%(affricative) in male voice respectively. Also, I obtain a high quality approximation-synthesis waveforms within TSIUVC by using frequency information of 0.547kHz below and 2.813kHz above. I evaluate MPC by using switching information of voiced/unvoiced and FBD-MPC by using switching information of voiced/Silence/TSIUVC. As, a result, I knew that synthesis speech of FBD-MPC was better in speech quality than synthesis speech of the MPC.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1299-1304
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• 2000

In a speed coding system using excitation source of voiced and unvoiced, it would be involved a distortion of speech quality in case coexist with a voiced and an unvoiced consonants in a frame. So, I propose TSIUVC(Transition Segment Including UnVoiced Consonant) searching, extraction ad approximation-synthesis method in order to uncoexistent with a voiced and unvoiced consonants in a frame. This method based on a zerocrossing rate and pitch detector using FIR-STREAK Digital Filter. As a result, the extraction rates of TSIUVC are 84.8% (plosive), 94.9%(fricative), 92.3%(affricative) in female voice, and 88%(plosive), 94.9%(fricative), 92.3%(affricative) in male voice respectively, Also, I obain a high quality approximation-synthesis waveforms within TSIUVC by using frequency information of 0.547kHz below and 2.813kHz above. This method has the capability of being applied to speech coding of low bit rate, speech analysis and speech synthesis.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.167-173
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• 2005

In a speech coding system using excitation source of voiced and unvoiced, it would be involved a distortion of speech quality in case coexist with a voiced and unvoiced consonants in a frame. So, I propose TSIUVC(Transition Segment Including Unvoiced Consonant) extraction method by using pitch pulses and Zero Crossing Rate in order to unexistent with a voiced and unvoiced consonants in a frame. And this paper present a TSIUVC approximate-synthesis method by using frequency band division. As a result, this method obtains a high quality approximation-synthesis waveform within TSIUVC by using frequency information of 0.547kHz below and 2.813kHz above. And the TSIUVC extraction rate was $91\%$ for female voice and $96.2\%$ for male voice respectively This method has the capability of being applied to a new speech coding of Voiced/Silence/TSIUVC, speech analysis, and speech synthesis.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.55-61
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• 2013

In this paper, we describe design and implementation of audio encoder/decoder for voice synthesis. It uses the encoding of difference value of successive samples instead of the original sample value. and has the compression ratio of 4. The function is verified by using FPGA and the performance is measured by the fabricated chip using $0.35{\mu}m$ standard CMOS process. The system clock is 16.384MHz. The measured THD+n is from -40dB to -80dB with frequency variation and the power consumption is about 80mW. It is suited for the mobile application of high audio quality and low power consumption.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.49-53
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• 2016

Recently, the use of signal compression methods to improve the efficiency of wireless networks have increased. In particular, the MPC system was used in the pitch extraction method and the excitation source of voiced and unvoiced to reduce the bit rate. In general, the MPC system using an excitation source of voiced and unvoiced would result in a distortion of the synthesis speech waveform in the case of voiced and unvoiced consonants in a frame. This is caused by normalization of the synthesis speech waveform in the process of restoring the multi-pulses of the representation segment. This paper presents an ACFBD-MPC (Amplitude Compensation Frequency Band Division-Multi Pulse Coding) using amplitude compensation in a multi-pulses each pitch interval and specific frequency to reduce the distortion of the synthesis speech waveform. The experiments were performed with 16 sentences of male and female voices. The voice signal was A/D converted to 10kHz 12bit. In addition, the ACFBD-MPC system was realized and the SNR of the ACFBD-MPC estimated in the coding condition of 8kbps. As a result, the SNR of ACFBD-MPC was 13.6dB for the female voice and 14.2dB for the male voice. The ACFBD-MPC improved the male and female voice by 1 dB and 0.9 dB, respectively, compared to the traditional MPC. This method is expected to be used for cellular telephones and smartphones using the excitation source with a low bit rate.