• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.881-883
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• 1987

This paper decribes a new technique for the generation of excitation sources in LPC system. We synthesize a speech signal using several excitation sources, according to residual signal energy and ZCR(zero Crossing Rate). One of the excitation sources mix the double differentiated glottal wave form source and noise source. As a result, we got improved speech signal than that produced by conventional LPC system.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1103-1106
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• 1999

Telegram is an indispensible information & telecommunication system to our daily life. VTS(Voice Telegram System) under intensive research is intended to enhance exchanging capability of information & telecommunication by adding voice media to existing telegram system. Overall configuration and necessary core technologies of the system were investigated for its development. Among those many technologies in need, the technology of compressing and recording data is most critical to the development of cheap hardware. This is so called vocoder algorithm and is the core technology of voice information system. So, here, vocoder algorithm now being studied will be introduced.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.233-238
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• 2005

In general CELP(Code Excited Linear Prediction) type vocoders provide good speech qualify around 4.8kbps. Among them, G.723.1 developed for Internet Phone and video-conferencing includes two vocoders, 5.3kbps ACELP(Algebraic-CELP) and 6.3kbps MP-MLQ(Multi-Pulse Maximum Likelihood Quantization) In order to improve the speech qualify in CELP vocoder, in this paper. we proposed a new spectrum analysis algorithm with variable window In CELP vocoder, the spectrum of the synthesised speech signal is distorted because the fixed size windows is used for spectrum analysis. So we have measured the spectral leakage and in order to minimize the spectral leakage have adjusted the window size. Applying this method G.723.1 ACELP, we can got SD(Spectral Distortion) reduction 0.084(dB), residual energy reduction 6.3$\%$ and MOS(Mean Opinion Score) improvement 0.1.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.78-83
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• 2000

Vocoders used in digital mobile phone adopt new improved algorithm to achieve better communication quality. Therefore the communication problem occurs between mobile phones using different vocoder algorithms. In this paper, the efficient implementation of 8kbps and 13kbps QCELP into one DSP chip to solve this problem is presented. We also describe the optimization method at each level, that is, algorithm-level, equation-level, and coding-level, to reduce the complexity for the QCELP vocoder algorithm implementation. The complexity in the codebook search-loop that is the main part for the QCELP algorithm complexity can be reduced about 50% by using these optimizations. The QCELP implementation with our DSP requires only 25 MIPS of computation for the 8kbps and 33 MIPS for the 13kbps ones. The DSP for our real-time implementation is a 16-bit fixed-point one specifically designed for vocoder applications and has a simple architecture compared to general-purpose ones in order to reduce the power consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.81-89
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• 2003

For improving the performance of noise suppression in tactical communication environments, an enhanced MELP vocoder is suggested, in which an acoustic noise suppressor is integrated into the front end of the MELP algorithm, and an FEC code into the channel side of the MELP algorithm. The acoustic noise suppressor is the modified IS-127 EVRC noise suppressor which is adapted for the MELP vocoder. As for FEC, the turbo code, which consists of rate-113 encoding and BCJR-MAP decoding algorithm, is utilized. In acoustic noise environments, the lower the SNR becomes, the more the effects of noise suppression is increased. Moreover, The suggested system has greater noise suppression effects in stationary noise than in non-stationary noise, and shows its superiority by 0.24 in MOS test to the original MELP vocoder. When the interleave size is one MELP frame, BER 10-6 is accomplished at channel bit SNR 4.2 ㏈. The iteration of decoding at 3 times is suboptimal in its complexity vs. performance. Synthetic quality is realized as more than MOS 2.5 at channel bit SNR 2 ㏈ in subjective voice quality test, when the interleave size is one MELP frame and the iteration of decoding is more than 3 times.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.138-142
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• 2009

We propose an effective voice-phishing detection algorithm based on discriminative weight training. The detection of voice phishing is performed based on a Gaussian mixture model (GMM) incorporaiting minimum classification error (MCE) technique. Actually, the MCE technique is based on log-likelihood from the decoding parameter of the SMV(Selectable Mode Vocoder) directly extracted from the decoding process in the mobile phone. According to the experimental result, the proposed approach is found to be effective for the voice phishing detection.

• Journal of IKEEE
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• v.13 no.4
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• pp.43-46
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• 2009

This paper deals with feeling recognition from people's voice to fine feature vectors. Voice signals include the people's own information and but also people's feelings and fatigues. So, many researches are being progressed to fine the feelings from people's voice. In this paper, We analysis Selectable Mode Vocoder(SMV) that is one of the standard 3GPP2 codecs of ETSI. From the analyzed result, we propose voices features for recognizing feelings. And then, feeling recognition algorithm based on gaussian mixture model(GMM) is proposed. It uses feature vectors is suggested. We verify the performance of this algorithm from changing the mixture component.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3E
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• pp.18-24
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• 2001

Speaking rate represents how many phonemes in speech signal have in limited time. It is various and changeable depending on the speakers and the characters of each phoneme. The preprocessing to remove the effect of variety of speaking rate is necessary before recognizing the speech in the present speech recognition systems. So if it is possible to estimate the speaking rate in advance, the performance of speech recognition can be higher. However, the conventional speech vocoder decides the transmission rate for analyzing the fixed period no regardless of the variety rate of phoneme but if the speaking rate can be estimated in advance, it is very important information of speech to use in speech coding part as well. It increases the quality of sound in vocoder as well as applies the variable transmission rate. In this paper, we propose the method for presenting the speaking rate as parameter in speech vocoder. To estimate the speaking rate, the variety of phoneme is estimated and the Line Spectrum Pairs is used to estimate it. As a result of comparing the speaking rate performance with the proposed algorithm and passivity method worked by eye, error between two methods is 5.38% about fast utterance and 1.78% about slow utterance and the accuracy between two methods is 98% about slow utterance and 94% about fast utterances in 30 dB SNR and 10 dB SNR respectively.

• Journal of Advanced Navigation Technology
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• v.11 no.1
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• pp.87-92
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• 2007

The conventional CELP(code excited linear prediction) type vocoder has no V/UV(voiced/unvoiced) classifier. So, the unvoiced speech is processed like the voiced speech. In this paper, to reduce the bit rate, we propose a new V/UV decision algorithm minimized error rate and preprocessing computation. This V/UV classifier use the LSP(line spectrum pair) parameter which is acquired spectrum analysis process in CELP vocoders. Applying this method to the 5.3kbps ACELP(algebraic code excited linear prediction) in the G.723.1, we can get the transmission bits rate reduction of 6% approximately without degradation of speech quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.111-117
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• 2008

In this paper, we propose an approach to improve the performance of voiced/unvoiced (V/UV) decision under background noise environments for the selectable mode vocoder (SMV) of 3GPP2. We first present an effective analysis of the features and the classification method adopted in the SMV. And then feature vectors which are applied to the GMM are selected from relevant parameters of the SMV for the efficient voiced/unvoiced classification. For the purpose of evaluating the performance of the proposed algorithm, different experiments were carried out under various noise environments and yields better results compared with the conventional scheme of the SMV.