Automatic Speech Recognition Based on Clustering Technique

Accurate Reader Identification for the Arabic Holy Quran Recitations Based on an Enhanced VQ Algorithm

“…However, most of these research studies either did not emphasize their results on the Arabic dialect or did not formally compare to other techniques' results. Indeed, methods such as VQ and k-means clustering algorithms for English speakers were presented previously in such systems [10,11].…”

“…Debnath and Roy [10] presented a clustering topology in automatic speech recognition (ASR) to recognize the spoken digits by speakers. They intended to allow computers to identify the English words that any humans had spoken.…”

“…(9) Repeat all these steps for each codebook in the codebook database. (10) If the candidates' reciter array is not empty, the recognized reciter is the reciter with the least total SEDs; otherwise, the reciter is not identified as one in the codebook database.…”

“…Furthermore, the proposed algorithm performance evaluation metrics (precision and recall) were computed in Eqns. ( 9) to (10) [35].…”

“…Thus, the target system must analyze the reciter's voice to decide the reading correctness. Indeed, the reciter's voice includes features that belong to the reciter's identity and the read text [10]. Therefore, one of the critical problems is establishing unique speech and language characteristics for each speaker separately.…”