Precise Segmentation Results Research Articles

Phonemic segmentation for continuous Mandarin speech recognition.

An algorithm is proposed in this paper for phonemic segmentation to improve the performance of a continuous Mandarin speech recognition systems. The coefficient of time variation of spectral envelope and the coefficient of tirrie. variation of zero order cepstrum are extracted using Unbiased Estimation of Log Spectrum (UELS). The parameter curves based on these coefficients are very smooth, therefore, the relation between parameter's maximum values and phoneme boundaries are easy to be found. By these smooth curves, the maximum value can be used as a criterion to delimit phonemes, rather than the threshold that is used in conventional systems, hence it is possible to get precise segmentation results. 300 sentences were used for an experiment, and the results show the system performance is better than traditional methods. The average phoneme-deletion rate is 1.3%, average phonemeinsertion rate is 3%. For evaluation, the segmentation results were used for a phoneme recognition experiment. 95.5% consonants recognition rate and 92.5% vowel recognition rate were obtained. The results show the approach is highly effective.

A comparison of four segmentation algorithms in the context of agricultural remote sensing

Four segmentation algorithms were tested and evaluated for their application to agricultural remote sensing image data. Each of the four algorithms were distinctly different in their concept and mode of operation. The operation of these four algorithms, the selection criteria, and the evaluation procedure are described. The results of the evaluation show that two of the algorithms, a hierarchial stepwise optimisation algorithms and a modified version of this same algorithm gave the most precise segmentation results.