Abstract
We present an ASR based pipeline for Amharic that orchestrates NLP components within a cross media analysis framework (CMAF). One of the major challenges that are inherently associated with CMAFs is effectively addressing multi-lingual issues. As a result, many languages remain under-resourced and fail to leverage out of available media analysis solutions. Although spoken natively by over 22 million people and there is an ever-increasing amount of Amharic multimedia content on the Web, querying them with simple text search is difficult. Searching for, especially audio/video content with simple key words, is even hard as they exist in their raw form. In this study, we introduce a spoken and textual content processing workflow into a CMAF for Amharic. We design an ASR-named entity recognition (NER) pipeline that includes three main components: ASR, a transliterator and NER. We explore various acoustic modeling techniques and develop an OpenNLP-based NER extractor along with a transliterator that interfaces between ASR and NER. The designed ASR-NER pipeline for Amharic promotes the multi-lingual support of CMAFs. Also, the state-of-the art design principles and techniques employed in this study shed light for other less-resourced languages, particularly the Semitic ones.- Anthology ID:
- 2020.sltu-1.42
- Volume:
- Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Dorothee Beermann, Laurent Besacier, Sakriani Sakti, Claudia Soria
- Venue:
- SLTU
- SIG:
- Publisher:
- European Language Resources association
- Note:
- Pages:
- 298–305
- Language:
- English
- URL:
- https://aclanthology.org/2020.sltu-1.42
- DOI:
- Cite (ACL):
- Yonas Woldemariam and Adam Dahlgren. 2020. Adapting Language Specific Components of Cross-Media Analysis Frameworks to Less-Resourced Languages: the Case of Amharic. In Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL), pages 298–305, Marseille, France. European Language Resources association.
- Cite (Informal):
- Adapting Language Specific Components of Cross-Media Analysis Frameworks to Less-Resourced Languages: the Case of Amharic (Woldemariam & Dahlgren, SLTU 2020)
- PDF:
- https://preview.aclanthology.org/emnlp22-frontmatter/2020.sltu-1.42.pdf