• Phonetics and Speech Sciences
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• v.7 no.3
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• pp.165-173
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• 2015

This study was aim to compare the phonological error patterns and PCC(Percentage of Correct Consonants) derived from the single word and spontaneous speech contexts of the speech sound disorders with unknown origin(SSD). The present study suggest that the development phonological error patterns and non-developmental error patterns of the target children, in according to speech context. The subjects were 15 children with SSD up to the age of 5 from 3 years of age. This research use 37 words of APAC(Assessment of Phonology & Articulation for Children) in the single word context and 100 eojeol in the spontaneous speech context. There was no difference of PCC between the single word and the spontaneous speech contexts. Significantly different developmental phonological error patterns between the single word and the spontaneous speech contexts were syllable deletion, word-medial onset deletion, liquid deletion, gliding, affrication, fricative other error, tensing, regressive assimilation. Significantly different non-developmental phonological error patterns were backing, addtion of phoneme, aspirating. The study showed that there was no difference of PCC between elicited single word and spontaneous conversational context. And there were some different phonological error patterns derived from the two contexts of the speech sound disorders. The more important interventions target is the error patterns of the spontaneous speech contexts for the immediate generalization and rising overall intelligibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.4
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• pp.484-490
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• 1990

In speech coding scheme, because information bits have different error sensitivities over channel errors, the channel coder for combining with speech coding should be realized by the variable coding rate considering the bit importance of speech information bits. In realizing the 4 kbps channel coder for 12kbps speech, this paper have chosen the channel coding method by analyzing the hard-decision post-decoding error rate of RCPC(Rate Compatible Punctured Convolutional) codes and bit error sensitivity of 12 kbps speech. Under the coherent QPSK and Rayleigh fading channel, the performance analysis has showed that 10dB gain was obtained in speech SEGSNR by 4-level uneuqal error protection, which was compared with the caseof no channel coding at 7dB channel SNR.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.137-142
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• 2013

Speech recognition system is input of inaccurate vocabulary by feature extraction case of recognition by appear result of unrecognized or similar phoneme recognized. Therefore, in this paper, we propose a speech recognition error correction method using phoneme similarity rate and reliability measures based on the characteristics of the phonemes. Phonemes similarity rate was phoneme of learning model obtained used MFCC and LPC feature extraction method, measured with reliability rate. Minimize the error to be unrecognized by measuring the rate of similar phonemes and reliability. Turned out to error speech in the process of speech recognition was error compensation performed. In this paper, the result of applying the proposed system showed a recognition rate of 98.3%, error compensation rate 95.5% in the speech recognition.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.171-176
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• 2023

This study is about a speech recognition error correction system designed to detect and correct speech recognition errors before natural language processing to increase the success rate of intent analysis in natural language processing with optimal efficiency in various service domains. An encoder is constructed to embedded the correct speech token and one or more error speech tokens corresponding to the correct speech token so that they are all located in a dense vector space for each correct token with similar vector values. One or more utterance tokens within a preset Manhattan distance based on the correct utterance token in the dense vector space for each embedded correct utterance token are detected through an error detector, and the correct answer closest to the detected error utterance token is based on the Manhattan distance. Errors are corrected by extracting the utterance token as the correct answer.

• Speech Sciences
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• v.10 no.2
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• pp.77-84
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• 2003

In this research, we seek the beginning of the speech and detect the stationary speech region using lip information. Performing running average of the estimated speech signal in the stationary region, we reduce the effect of musical noise which is inherent to the conventional MlMSE (Minimum Mean Square Error) speech enhancement algorithm. In addition to it, SFM (Spectral Flatness Measure) is incorporated to reduce the speech signal estimation error due to speaking habit and some lacking lip information. The proposed algorithm with Wiener filtering shows the superior performance to the conventional methods according to MOS (Mean Opinion Score) test.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.394-400
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• 2002

In digital speech communications, the quality of service can be increased by speech coding scheme that is adaptive to the error rate of voice packet transmission. However, current communication protocol in cellular and internet communications does not provide the function that transmits the channel error information. To solute this problem, in this paper, new method for real-time transmission of channel error information is proposed, where channel error information is embedded in voice packet. The proposed method utilizes the pulse positions of codevector in ACELP speech codec, which results in little degradation in speech quality and low false alarm rate. The simulations with various speech data show that the proposed method meets the requirement in speech quality, detection rate, and false alarm rate.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.177-180
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• 2007

We compared CS-ACELP with QCELP speech coder in CDMA cellular under channel error environment and experimented performance with its measured value under channel error environment. Also, we specified the effective coding scheme to overcome. CS-ACELP speech coder using a LSP vector quantizer shows transparent speech quality from the results that SD is 0.92dB and outlier frames over 2dB is 2.9% in the BER 0.10% condition. CS-ACELP speech coder which is utilizing MA predictor shows better results on SVR and SEGSNR than QCELP speech coder(IS-96) adopting DPCM type predictor when bit error occurs from BER 0.01% to 0.50%.

• Proceedings of the Acoustical Society of Korea Conference
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• 1984.12a
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• pp.66-69
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• 1984

This paper is a study on the Endpoint Detection for Korean Speech Recognition. In speech signal process, analysis parameter was classification from Zero Crossing Rate(Z.C.R), Log Energy(L.E), Energy in the predictive error(Ep) and fundamental Korean Speech digits, /영/-/구/ are selected as date for the Recognition of Speech. The main goal of this paper is to develop techniques and system for Speech input ot machine. In order to detect the Endpoint, this paper makes choice of Log Energy(L.E) from various parameters analysis, and the Log Energy is very effective parameter in classifying speech and nonspeech segments. The error rate of 1.43% result from the analysis.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.198-202
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• 1988

In digital mobile communications received speech data are affected by burst errors as well as random errors. To overcome these errors we propose a bit-selective forward error correction scheme for the speech data which is sub-band coded at 13 kbps and transmitted over a 16 kbps channel. For a few error correcting codes the signal-to-noise ratio of error-corrected speech is obtained and compared through the simulation of mobile communication channels.