Using 25-30 seconds of audio per speaker from 100 rural Bhojpuri women, synthetic speech augmentation cuts ASR word error on the new SRUTI benchmark by 4.7 points.
English-Bhojpuri SMT System: Insights from the Karaka Model
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abstract
This thesis has been divided into six chapters namely: Introduction, Karaka Model and it impacts on Dependency Parsing, LT Resources for Bhojpuri, English-Bhojpuri SMT System: Experiment, Evaluation of EB-SMT System, and Conclusion. Chapter one introduces this PhD research by detailing the motivation of the study, the methodology used for the study and the literature review of the existing MT related work in Indian Languages. Chapter two talks of the theoretical background of Karaka and Karaka model. Along with this, it talks about previous related work. It also discusses the impacts of the Karaka model in NLP and dependency parsing. It compares Karaka dependency and Universal Dependency. It also presents a brief idea of the implementation of these models in the SMT system for English-Bhojpuri language pair.
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Recognizing Every Voice: Towards Inclusive ASR for Rural Bhojpuri Women
Using 25-30 seconds of audio per speaker from 100 rural Bhojpuri women, synthetic speech augmentation cuts ASR word error on the new SRUTI benchmark by 4.7 points.