• Proceedings of the Korean Magnestics Society Conference
• /
• 2008.12a
• /
• pp.283.1-283.1
• /
• 2008

• Proceedings of the Korean Magnestics Society Conference
• /
• 2008.12a
• /
• pp.30.2-30.2
• /
• 2008

• MALSORI
• /
• no.52
• /
• pp.145-160
• /
• 2004

In this paper, a new noise compensation method based on the eigenvoice framework in feature space is proposed to reduce the mismatch between training and testing environments. The difference between clean and noisy environments is represented by the linear combination of K eigenvectors that represent the variation among environments. In the proposed method, the performance improvement of speech recognition systems is largely affected by how to construct the noisy models and the bias vector set. In this paper, two methods, the one based on MAP adaptation method and the other using stereo DB, are proposed to construct the noisy models. In experiments using Aurora 2 DB, we obtained 44.86% relative improvement with eigen-environment method in comparison with baseline system. Especially, in clean condition training mode, our proposed method yielded 66.74% relative improvement, which is better performance than several methods previously proposed in Aurora project.

• MALSORI
• /
• no.53
• /
• pp.103-118
• /
• 2005

The performance of speech recognition system is degraded by mismatch between training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE) was introduced to overcome environmental mismatch using stereo data. In this paper, we propose several methods to improve the conventional SPLICE and evaluate them in the Aurora2 task. We generalize SPLICE to compensate for covariance matrix as well as mean vector in the feature space, and thereby yielding the error rate reduction of 48.93%. We also employ the weighted sum of correction vectors using posterior probabilities of all Gaussians, and the error rate reduction of 48.62% is achieved. With the combination of the above two methods, the error rate is reduced by 49.61% from the Aurora2 baseline system.

• The Journal of the Acoustical Society of Korea
• /
• v.31 no.2
• /
• pp.87-92
• /
• 2012

In this paper, a robust feature compensation method to deal with the environmental mismatch is proposed. The proposed method applies energy based weights according to the degree of speech presence to the Mean subtraction, Variance normalization, and ARMA filtering (MVA) processing. The weights are further smoothed by the moving average and maximum filters. The proposed feature compensation algorithm is evaluated on AURORA 2 task and distant talking experiment using the robot platform, and we obtain error rate reduction of 14.4 % and 44.9 % by using the proposed algorithm comparing with MVA processing on AURORA 2 task and distant talking experiment, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.10a
• /
• pp.379-382
• /
• 2008

In order to reduce the noise quantity in a conversation under the noisy environment, it is necessary for the signal processing system to process adaptively according to the noise quantity in order to enhance the performance. There fore this paper presents a recognition method for noise quantity by linear predictive coefficient using a three layered neural network, which is trained using three kinds of speech that is degraded by various background noises. In the experiment, the average values of the recognition results were 97.6% or more for various noises using Aurora2 database.

• Speech Sciences
• /
• v.10 no.3
• /
• pp.263-277
• /
• 2003

One of major problems in speech recognition is performance degradation due to the mismatch between the training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE), which is frame-based bias removal algorithm for cepstral enhancement using stereo training data and noisy speech model as a mixture of Gaussians, was proposed and showed good performance in noisy environments. In this paper, we propose several methods to improve the conventional SPLICE. First we apply Cepstral Mean Subtraction (CMS) as a preprocessor to SPLICE, instead of applying it as a postprocessor. Secondly, to compensate residual distortion after SPLICE processing, two-stage SPLICE is proposed. Thirdly we employ phonetic information for training SPLICE model. According to experiments on the Aurora 2 database, proposed method outperformed the conventional SPLICE and we achieved a 50% decrease in word error rate over the Aurora baseline system.

• Proceedings of the Zoological Society Korea Conference
• /
• 2000.04a
• /
• pp.82.2-82
• /
• 2000

No Abstract, See Full Text

• The Korean Journal of Physiology and Pharmacology
• /
• v.23 no.5
• /
• pp.393-402
• /
• 2019

Aurora kinases inhibitors, including ZM447439 (ZM), which suppress cell division, have attracted a great deal of attention as potential novel anti-cancer drugs. Several recent studies have confirmed the anti-cancer effects of ZM in various cancer cell lines. However, there have been no studies regarding the cardiac safety of this agent. We performed several cytotoxicity, invasion and migration assays to examine the anti-cancer effects of ZM. To evaluate the potential effects of ZM on cardiac repolarisation, whole-cell patch-clamp experiments were performed with human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and cells with heterogeneous cardiac ion channel expression. We also conducted a contractility assay with rat ventricular myocytes to determine the effects of ZM on myocardial contraction and/or relaxation. In tests to determine in vitro efficacy, ZM inhibited the proliferation of A549, H1299 (lung cancer), MCF-7 (breast cancer) and HepG2 (hepatoma) cell lines with $IC_{50}$ in the submicromolar range, and attenuated the invasive and metastatic capacity of A549 cells. In cardiac toxicity testing, ZM did not significantly affect $I_{Na}$, $I_{Ks}$ or $I_{K1}$, but decreased $I_{hERG}$ in a dose-dependent manner ($IC_{50}$: $6.53{\mu}M$). In action potential (AP) assay using hiPSC-CMs, ZM did not induce any changes in AP parameters up to $3{\mu}M$, but it at $10{\mu}M$ induced prolongation of AP duration. In summary, ZM showed potent broad-spectrum anti-tumor activity, but relatively low levels of cardiac side effects compared to the effective doses to tumor. Therefore, ZM has a potential to be a candidate as an anti-cancer with low cardiac toxicity.

• Bulletin of the Korean Space Science Society
• /
• 1996.05a
• /
• pp.28-28
• /
• 1996

No Abstract, See Full Text