• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.68-71
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• 1985

In this paper, Sentence-Sip E Il Ka Gi Seo U1 E Gan Da was spoken by 4 men and 3 see sound is used for the experiment. A/D conversion time is 30 sec. Data are obtained using the microcomputer and compressed by ADPCM Rate of compression is 1/8. Data compressed by ADPCM are synthesized and compared to the original sound. Rate of speech identification is analysed using the sound pressure, white noise. Coding of ADPCM is done for 5bit. As the result of fixing starting voltage by 2.6V. It is acertained that variable value increases in initial speech signal and then process is made by minimum value "3". From the result of processing, synthesized sound is almost eaual to original sound. Minimum values cause distorition, Dummy Head System is used in this experiment.xperiment.

• Speech Sciences
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• v.11 no.3
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• pp.175-180
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• 2004

In case of the hearing impairment with tinnitus and increased sound sensitivity, it is known that the patients tend to appeal the psychologically oriented social handicap rather than communication disability. The audiologist who is responsible for such patients in aural rehabilitation should pay special attention to the counseling techniques including tinnitus retain therapy (TRT), ear protector, noise generator, or specific acoustic training based on close cooperation and rapport. And then the audiologist should try to lessen their reaction to the tinnitus by using a hearing aid. This therapies tries to focus not a. total approach but a treatment to lessen the severity of tinnitus. This paper as a case report that a unilateral sharply slopped sensorineural hearing impaired person with tinnitus and increased sound sensitivity by using four channel digital signal processing (DSP) hearing aid with programming increment at low level (PILL).

• MALSORI
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• no.49
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• pp.145-158
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• 2004

This paper is aiming at implementation of real-time speaker verification system using DSP board. Dialog/4, which is based on microprocessor and DSP processor, is selected to easily control telephone signals and to process audio/voice signals. Speaker verification system performs signal processing and feature extraction after receiving voice and its ID. Then through computing the likelihood ratio of claimed speaker model to the background model, it makes real-time decision on acceptance or rejection. For the verification experiments, total 15 speaker models and 6 background models are adopted. The experimental results show that verification accuracy rates are 99.5% for using telephone speech-based speaker models.

• MALSORI
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• no.66
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• pp.73-86
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• 2008

Beamforming is one of the spatial filtering techniques which extract only desired signals from noisy environments using microphone arrays. Fixed beamforming is a simple concept and easy to implement. However, it does not show good performance in real noisy conditions. As an adaptive beamforming, Frost algorithm can be a good candidate. It uses the concept of the linearly constrained minimum variance (LCMV) algorithm. The difference between the Frost and the LCMV algorithm is the error correction scheme which is very effective feature in the aspect of performance. In this paper, as quadrature mirror filtering (QMF)-based filterbank is utilized as the pre-processing of the Frost beamformning, the filter length and the learning rate of each band is optimized to improve the performance. The performance is measured by the signal-to-noise ratio (SNR) and the Bark's scale spectral distortion (BSD).

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3150-3152
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• 1999

The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical information processing systems. Typically under realistic circumstances, the encoding and communication of message has to deal with different sources of noise and disturbances. In this paper, I propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In this paper, based on the robust vector quantization I have an experiment about speech coding.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.5
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• pp.62-70
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• 2000

In this study, speech recognition for Korean digit is performed using filter bank which is programmed discrete HMM and DTW. Spectral analysis reveals speech signal features which are mainly due to the shape of the vocal tract. And spectral feature of speech are generally obtained as the exit of filter banks, which properly integrated a spectrum at defined frequency ranges. A set of 8 band pass filters is generally used since it simulates human ear processing. And defined frequency ranges are 320-330, 450-460, 640-650, 840-850, 900-1000, 1100-1200, 2000-2100, 3900-4000Hz and then sampled at 8kHz of sampling rate. Frame width is 20ms and period is 10ms. Accordingly, we found that the recognition rate of DTW is better than HMM for Korean digit speech in the experimental result. Recognition accuracy of Korean digit speech using filter bank is 93.3% for the 24th BPF, 89.1% for the 16th BPF and 88.9% for the 8th BPF of hardware realization of voice dialing system.

• The Transactions of the Korea Information Processing Society
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• v.7 no.7
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• pp.2246-2253
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• 2000

In this paper, we show that one can enhance the performance of blind segmentation of phoneme boundaries by adopting the knowledge of Korean syllabic structure and the regions of voiced/unvoiced sounds. eh proposed method consists of three processes : the process to extract candidate phoneme boundaries, the process to detect boundaries of voiced/unvoiced sounds, and the process to select final phoneme boundaries. The candidate phoneme boudaries are extracted by clustering method based on similarity between two adjacent clusters. The employed similarity measure in this a process is the ratio of the probability density of adjacent clusters. To detect he boundaries of voiced/unvoiced sounds, we first compute the power density spectrum of speech signal in 0∼400 Hz frequency band. Then the points where this paper density spectrum variation is greater than the threshold are chosen as the boundaries of voiced/unvoiced sounds. The final phoneme boundaries consist of all the candidate phoneme boundaries in voiced region and limited number of candidate phoneme boundaries in unvoiced region. The experimental result showed about 40% decrease of insertion rate compared to the blind segmentation method we adopted.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.595-602
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• 2008

The focused word of each sentence is a help in recognizing and understanding spoken Korean. To find the method of focused word spotting at spoken speech signal, we made an analysis of the average and variance of Fundamental Frequency and the average energy extracted from a focused word and the other words in a sentence by experiments with the speech data from 100 spoken sentences. The result showed that focused words have either higher relative average F0 or higher relative variances of F0 than other words. Our findings are to make a contribution to getting prosodic characteristics of spoken Korean and keyword extraction based on natural language processing.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.217-223
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• 2009

Vocabulary recognition system of Mobile terminal is executed statistical method for vocabulary recognition and used statistical grammar recognition system using N-gram. If limit arithmetic processing capacity in memory of vocabulary to grow then vocabulary recognition algorithm complicated and need a large scale search space and many processing time on account of impossible to process. This study suggest vocabulary recognition optimize using MLHF System. MLHF separate acoustic search and lexical search system using FLaVoR. Acoustic search feature vector of speech signal extract using HMM, lexical search recognition execution using Levenshtein distance algorithm. System performance as a result of represent vocabulary dependence recognition rate of 98.63%, vocabulary independence recognition rate of 97.91%, represent recognition speed of 1.61 second.