استفاده متوالی از مدل های طیفی برای کاهش اشتباهات حذف و درج در تشخیص واکه

Experiments are separately conducted on three standard speech corpora, namely FARSDAT, TIMIT and TFARSDAT. The effectiveness of the techniques proposed to reduce three types of detection errors is verified. The criteria of total error (as the summation of three detection errors) and F-measure, respectively result in about 9.7% and 95.1% for FARSDAT, 17.5% and 91.3% for TIMIT, and 19.6% and 90.2% for the TFARSDAT corpus. The evaluation results show that the proposed framework outperforms the existing well-known methods in terms of both total error and F-measure on both read and spontaneous speech corpora.