Syllable-Based Text-To- Speech Synthesis (Tts) for Amharic
| dc.contributor.advisor | Abebe, Ermias (PhD) | |
| dc.contributor.author | Wordofa, Mulualem | |
| dc.date.accessioned | 2018-11-29T13:19:56Z | |
| dc.date.accessioned | 2023-11-29T04:56:48Z | |
| dc.date.available | 2018-11-29T13:19:56Z | |
| dc.date.available | 2023-11-29T04:56:48Z | |
| dc.date.issued | 2013-06 | |
| dc.description.abstract | We have experienced an exponential increase in the electronic Amharic text information inside and outside of the organization. This accumulation of information is challenging for archival and searching of information. Due to that, an information retrieval (IR) system for Amharic language become indispensible and it allows the user to retrieve relevant documents that satisfies information need of users. Some Amharic IR systems were developed in the last couples of decade, however, the performance measure of the systems were not adorable. It happened because of different reasons but the major one was not properly address semantic natures of the language. Moreover, there was no any attempt to make retrieval effective through document clustering. In order to solve these issues, integrating of semantic indexing of documents and document clustering techniques with generic IR system will improve the retrieval performance. Methods: In this research semantic indexing and document clustering of Amharic IR system is developed. It comprises three basic components indexing, clustering and searching. The system comprises all processes exist in generic IR plus to that C-value technique multi word term extraction, k-means algorithms document clustering, cluster base searching strategy used. Conclusion: The system tested using tagged Amharic news documents size of 650Kb and it registered F-measure of 66% accuracy. It is by far good compared with the latest work (Amanuel[31] work). Nevertheless, the performance of the system is greatly affected by synonyms and polysemous, incorrect clustering, cluster representative problems, Amharic knowledge base. Keywords: Information Retrieval, Semantic indexing, Document Clustering, Amharic | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/14696 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Information Retrieval | en_US |
| dc.subject | Semantic indexing | en_US |
| dc.subject | Document ClusteringAmharic | en_US |
| dc.title | Syllable-Based Text-To- Speech Synthesis (Tts) for Amharic | en_US |
| dc.type | Thesis | en_US |