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Details van artikel 14 van 58 gevonden artikelen
| Titel: |
CASRA+: A Colloquial Arabic Speech Recognition Application |
| Auteur: |
Ramzi A. Haraty Omar El Ariss |
| Verschenen in: |
American journal of applied sciences |
| Paginering: | Jaargang 4 (2007) nr. 1 pagina's 23-32 |
| Jaar: |
2007 |
| Inhoud: |
The research proposed here was for an Arabic speech recognition application, concentrating onthe Lebanese dialect. The system starts by sampling the speech, which was the process of transforming thesound from analog to digital and then extracts the features by using the Mel-Frequency CepstralCoefficients (MFCC). The extracted features are then compared with the system's stored model; in this casethe stored model chosen was a phoneme-based model. This reference model differs from the direct wordtemplate matching, where speech features that are extracted from the input are directly compared to theword templates. Each word template in the direct matching model was stored as a vector of featureparameters. Thus, when the vocabulary size of the ASR system becomes large, the memory size for theword template will become humongous. In contrast, the model used here was phoneme-like templatematching. Word templates are stored as phoneme-like template parameters. Thus, the memory size for theword templates will not grow as fast as that of the direct matching model. |
| Uitgever: |
Science Publications (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 14 van 58 gevonden artikelen
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