• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.5-11
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• 1996

The purpose of this paper is to propose a method improving the performance of a semi-continuous hidden Markov model(SCHMM) speaker adaptation system which uses Bayesian Parameter reestimation approach. The performance of Bayesian speaker adaptation could be degraded in case that the features of a new speaker are severely different from those of a reference codebook. The excessive codewords of the reference codebook still remain after adaptation proess. which cause confusion in recognition process. To solve such problems, the proposed method uses formant information which is extracted from the cepstral coefficients of the reference codebook and adaptation data. The reference codebook is adapted to represent the formant distribution of a new speaker and it is used for Bayesian speaker adaptation as an initial codebook. The proposed method provides accurate correspondence between reference codebook and adaptation data. It was observed that the excessive codewords were not selected during recognition process. The experimental results showed that the proposed method improved the recognition performance.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.313-322
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• 2005

In order to access digital items in a server via ubiquitous devices, the digital items should be adapted according to the system environment, device characteristics and user preferences. In ubiquitous environment, those device-dependent adaptation requirements are not statically determined and not predictable. Therefore an application specific adaptation mechanism can not be applied to a general digital item adaptation engine. In this paper, we propose an application independent digital item adaptation architecture which has a set of minimal transcoders, transcoding path generator for a required adaptation requirement, and adaptation scheduler. And a CFG based method of finding a sequence of multiple unit transcoders called a transcoding path Is described in detail followed by experimental results.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.10
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• pp.17-25
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• 2005

A grid adaptation method within systems of chimera and patched grids is presented. Problem domains are divided into near-body and off-body fields. Near-body field is filled with curvilinear body-fitted grids that extend only a short distance from body surfaces and connected to other grid systems via chimera domain connectivity method. Off-body field is filled with patched uniform cartesian grids of varying levels of refinement. This method gives flexibility in grid generation and efficient adaptation capability. Several numerical experiments including 2D store separation were performed to show the performance of the proposed adaptation method.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.339-342
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• 1998

In this paper, we proposed various speaker adaptation methods and studied the performance of these methods. Methods which were studied in this paper are MAPE(Maximum A Posteriori Probability Estimation), ARTMAP. In order to evaluate the performance of these methods, we used Korean isolated digits as the experimental data, the hybrid speaker adaptation method, which unfied MAPE, linear spectral estimating and outpur probability of SCHMM, showed the better recognition result than those which performed other methods. And the method using ARTMAP showed the similar result to above hybrid method.

• Asian Journal of Innovation and Policy
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• v.9 no.1
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• pp.36-55
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• 2020

Climate change is one of the most discussed issues in international for a today. Evaluating the effect of climate change at a regional level and setting up an appropriate policy to address the issues associated with climate change require a proper evaluation process on the climate change and adaptation projects already implemented. Although various evaluation approaches to climate change adaptation programs have been proposed, it is rare to find a proper systematic approach to evaluating the reliability of those climate change adaptation programs. In the current situation regarding the system to evaluate climate change adaptation programs, the purpose of this study is to suggest a theoretical and standardized evaluation system on the reliability of climate change adaptation schemes. The new approach suggested in this paper will be appropriate when requiring a confidence level for adaptation programs that are specially localized and categorized. Using various quantitative and qualitative evaluation methods with the inherent reality mechanism, we provide a conceptual framework to measure the reliability of climate change adaptation programs with a flexible adjustment process. With the proposed framework, it is possible to provide the level of confidence on the results collected from the evaluation systems and construct a standardized, system-wide assessment procedure toward climate change adaptation policies. By applying this approach based on scientific evidence on the reliability of climate change adaptation policies, appropriate and efficient climate change adaptation programs will be properly designed for and implemented in Korea.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.383-389
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• 2004

In this paper. we propose the bias compensation methods and the eigenvoice method using the mean of dimensional eigenvoice to improve the performance of rapid speaker adaptation based on eigenvoice under mismatch between training and test environment. Experimental results for vocabulary-independent word recognition task (using PBW 452 DB) show that the proposed methods yield improvements for small adaptation data. We obtained about 22∼30% relative improvement by the bias compensation methods as amount of adaptation data varied from 1 to 50, and obtained 41% relative improvement in error rate by the eigenvoice method using the mean of dimensional eigenvoice with only single adaptation word.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.566-571
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• 2009

This paper proposes noise-robust fast speaker adaptation method based on the eigenvoice framework in various noisy environments. The proposed method is focused on de-noising and environment clustering. Since the de-noised adaptation DB still has residual noise in itself, environment clustering divides the noisy adaptation data into similar environments by a clustering method using the cepstral mean of non-speech segments as a feature vector. Then each adaptation data in the same cluster is used to build an environment-clustered speaker adapted (SA) model. After selecting multiple environmentally clustered SA models which are similar to test environment, the speaker adaptation based on an appropriate linear combination of clustered SA models is conducted. According to our experiments, we observe that the proposed method provides error rate reduction of $40{\sim}59%$ over baseline with speaker independent model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1243-1250
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• 2015

This paper presents an effective recognition method of VPI patient's speech for a VPI speech reconstruction system. Speaker adaptation technique is employed to improve VPI speech recognition. This paper proposes to use simulated speech for generating an initial model for speaker adaptation, in order to effectively utilize the small size of VPI speech for model adaptation. We obtain 83.60% in average word accuracy by applying MLLR for speaker adaptation. The proposed speaker adaptation method using simulated speech model brings 6.38% improvement in average accuracy. The experimental results demonstrate that the proposed speaker adaptation method is highly effective for developing recognition system of VPI speech which is not suitable for constructing large-size speech database.

• MALSORI
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• no.53
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• pp.143-156
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• 2005

Speaker adaptation in eigenvoice space is a popular method for rapid speaker adaptation. To improve the performance of the method, the number of speaker dependent models should be increased and eigenvoices should be re-estimated. However, principal component analysis takes much time to find eigenvoices, especially in a continuous speech recognition system. This paper describes a method to reduce computation time to estimate eigenvoices only for supplementary speaker dependent models and to merge them with the used eigenvoices. Experiment results show that the computation time is reduced by 73.7% while the performance is almost the same in case that the number of speaker dependent models is the same as used ones.

• MALSORI
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• no.58
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• pp.83-99
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• 2006

One key factor that hinders the widespread deployment of speaker identification technologies is the requirement of long enrollment utterances to guarantee low error rate during identification. To gain user acceptance of speaker identification technologies, adaptation algorithms that can enroll speakers with short utterances are highly essential. To this end, this paper applies MLLR speaker adaptation for speaker enrollment and compares its performance against other speaker modeling techniques: GMMs and HMM. Also, to speed up the computational procedure of identification, we apply speaker clustering method which uses principal component analysis (PCA) and weighted Euclidean distance as distance measurement. Experimental results show that MLLR adapted modeling method is most effective for short enrollment utterances and that the GMMs performs better when long utterances are available.