Boontee Kruatrachue

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This paper proposes an efficient acoustic model adaptation method based on the use of simulated-data in maximum likelihood linear regression (MLLR) adaptation for robust speech recognition. Online MLLR adaptation is an unsupervised process which requires an input speech with phone labels transcribed automatically. Instead of using only the input signal in(More)
A method of parallel-program optimization called grain packing is introduced that reduces total execution time of a parallel program by balancing execution time and communication time. The new method is applicable to both extended serial and concurrent programming languages, and can be used in languages such as OCCAM, Fortran, and Pascal. It is shown by(More)
This paper proposes a new environmental noise classification using principal component analysis (PCA) for robust speech recognition. Once the type of noise is identified, speech recognition performance can be enhanced by selecting the identified noise specific acoustic model. The proposed model applies PCA to a set of noise features, and results from PCA(More)
This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to(More)
This paper proposes an unconstrained handwritten Thai character recognition method using multiple representations. The proposed method can recognize different handwritten Thai characters having small curve segments with clockwise and counter clockwise directions, although the conventional method such as the elastic matching method was difficult to recognize(More)
This paper proposes the use of tree-structured model selection and simulated-data in maximum likelihood linear regression (MLLR) adaptation for environment and speaker robust speech recognition. The objective of this work is to solve major problems in robust speech recognition system, namely unknown speaker and unknown environmental noise. The proposed(More)