• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1635-1643
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• 1995

This paper proposes an algorithm for machine recognition of phonemes in continuously spoken Korean. The proposed algorithm is a static strategy neural network. The algorithm uses, at the stage of training neurons, features such as the rate of zero crossing, short-term energy, and either PARCOR or auditory-like perceptual linear prediction(PLP) but not both, covering a time of 171ms long. Numerical results show that the algorithm with PLP achieves approximately the frame-based phoneme recognition rate of 99% for small vocabulary recognition experiments. Based on this it is concluded that the proposed algorithm with PLP analysis is effective in phoneme recognition.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.494-500
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• 2008

In the field of development of human interface technology, the interactions between human and machine are important. The research on emotion recognition helps these interactions. This paper presents an algorithm for emotion recognition based on personalized speech signals. The proposed approach is trying to extract the characteristic of speech signal for emotion recognition using PLP (perceptual linear prediction) analysis. The PLP analysis technique was originally designed to suppress speaker dependent components in features used for automatic speech recognition, but later experiments demonstrated the efficiency of their use for speaker recognition tasks. So this paper proposed an algorithm that can easily evaluate the personal emotion from speech signals in real time using personalized emotion patterns that are made by PLP analysis. The experimental results show that the maximum recognition rate for the speaker dependant system is above 90%, whereas the average recognition rate is 75%. The proposed system has a simple structure and but efficient to be used in real time.

• Speech Sciences
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• v.6
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• pp.163-179
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• 1999

For the set up, management and repair of a mobile communication system, continuous estimation of speech quality is required. Speech quality measurement can be conducted by listener's judgement in a subjective test such as MOS (Mean Opinion Score) test. However, this method is laborious, expensive and time-consuming, it is advisable to predict subjective speech quality via objective measures. This paper presents a robust objective speech quality measure, PLP-CMS (Perceptual Linear Predictive-Cepstral Mean Subtraction), which can predict subjective speech quality in mobile communication systems. PLP-CMS has a high correlation with subjective quality owing to PLP (Perceptual Linear Predictive) analysis and shows a robust performance not being influenced by PSTN (Public Switched Telephone Network) channel effects due to CMS (Cepstral Mean Subtraction). To prove the performance of our proposed algorithm, we carried out subjective and objective quality estimation on speech samples which are variously distorted in a real mobile communication system. As a result, we demonstrated that PLP-CMS has a higher correlation with subjective quality than PSQM (Perceptual Speech Quality Measure) and PLP-CD (Perceptual Linear Predictive-Cepstral Distance).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.5
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• pp.609-616
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• 2007

Palletizing is necessary to promote the efficiency of storage and shipping tasks. These are, however some of the most monotonous, heavy and laborious tasks in the factory. Therefore many types of robot palletizing systems have been developed, but many robot motion commands still depend on the teaching pendent. That is, an operator inputs the motion command lines one by one. It is very troublesome, and most of all, the user must know how to type the code. That is why we propose a new GUI (Graphic User Interface) Palletizing System. To cope with this issue, we proposed a 'PLP' (Pallet Loading Problem) algorithm, Fast Algorithm and realize 3D auto-patterning visualization interface. Finally, we propose the robot palletizing simulator. Internally, the schematic of this simulator is as follows. First, an user inputs the physical information of object. Second, simulator calculates the optimal pattern for the object and visualizes the result. Finally, the calculated position data of object is passed to the robot simulator. To develop the robot simulator, we use an articulated robot, and analyze the kinematics and dynamics. Especially, All problem including thousands of boxes were completely calculated in less than 1 second and resulted in optimal solutions by the Fast Algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.17-30
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• 1992

This paper concerns with (p$_{1}$, p$_{2}$)-Plant Location problem in which entire set of candidate sites for facility locations is divided by two overlapping subsets, each of which with its own number of facilities to be established. We propose an algorithm which attempts to solve the Lagrangean dual of (p$_{1}$, p$_{2}$)-PLP by dividing sub-problem into twop-Plant Location Problems and solving them based on the convexity of the Lagrangean dual problem with respect to the number of facilities to be established. In doing so, Orthogonal Move procedure is proposed to provide easy-to-obtain lower bound to the Lagrangean Dual of (p$_{1}$, p$_{2}$)-PLP. Computational experience is reported.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.131-138
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• 2018

In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.184-187
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• 1995

This paper proposes an algorithm for machine recognition of phonemes in continuous speech. The proposed algorithm is static strategy neural network. The algorithm uses, at the stage of training neuron, features such as PARCOR coefficient and auditory-like perceptual liner prediction . These features are extracted from speech samples selected by a sliding 25.6msec windows with s sliding gap being 3 msec long, then interleaved and summed up to 7 sets of parmeters covering 171 msec worth of speech for use of neural inputs. Perfomances are compared when either PARCOR or auditory-like PLP is included in the feture set.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.3
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• pp.43-53
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• 2009

The pallet loading problem(PLP) requires the best orthogonal layout that loads the maximum number of identical boxes(small rectangle) onto a pallet(large rectangle). Since the high pallet utilization saves the distribution and storage costs, many heuristic and exact algorithms have been developed so far. Martins and Dell have found the optimal layouts for the all PLPs less than or equal to 100 boxes except for only 5 problems in their recent research. This paper defines the 'stair structure' and proposes a new exact algorithm applying it. In order to show the priority of the proposed algorithm, computational results are compared to previous algorithms and the optimal layouts for the S unsolved problems are given.

• MALSORI
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• no.51
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• pp.151-165
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• 2004

For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1137-1145
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• 2007

Palletizing tasks are necessary to promote efficient storage and shipping of boxed products. These tasks, however, involve some of the most monotonous and physically demanding labor in the factory. Thus, many types of robot palletizing systems have been developed, although many robot motion commands still depend on the teach pendant. That is, the operator inputs the motion command lines one by one. This is very troublesome and, most importantly, the user must know how to type the code. We propose a new GUI(Graphic User Interface) for the palletizing system that is more convenient. To do this, we used the PLP "Fast Algorithm" and 3-D auto-patterning visualization. The 3-D patterning process includes the following steps. First, an operator can identify the results of the task and edit them. Second, the operator passes the position values of objects to a robot simulator. Using those positions, a palletizing operation can be simulated. We chose a widely used industrial model and analyzed the kinematics and dynamics to create a robot simulator. In this paper we propose a 3-D patterning algorithm, 3-D robot-palletizing simulator, and modified trajectory generation algorithm, an "overlapped method" to reduce the computing load.