本 硏究에서는 韓國語 10개 도市名을 認識 對象으로 하였다. 各 單語는 男性 話者 10人에 의하여 5번씩 反復 發音한 500單語를 對象으로 하여 필터뱅크 出力을 抽出하여 認識 파라미터로 使用하였다. 필터뱅크는 RC 能動素子를 利用하여 200[Kz]부터 1/3 octave 間隔으로 15채널로 構成하였다. 基準音은 集團化 알고리즘에 의해 設定하였으며 類似度 比較를 위해 DTW 알고리즘을 利用하였다. 距離 計算式에 따른 認識結果를 把握하기 위하여 유크리드 式과 체비셔브 式을 使用하여 距離를 計算하였으며 認識 結果 각각 16.4[%], 15.0[%]의 誤認識率을 얻었다.
In this paper, 10 city names of Korean were recognized. The name are articulated each 5 times by 10 male speakers. Filter bank output on total 500 words were extracted and they were used as feature parameters. Filter bank was constructed of 15 channels with 1/3 octave spacing from 200[Hz], using RC active circuit. Reference templates were created by clustering algorithm. DTW algorithm was used to compare similarity between reference templates and input words. Euclidean distance equation and Chebyshev distance equation were used to know the distinction between the recognition results obtained by the method of distance caculation, error rates are 16.4[%], 15.0[%], respectively.
