Ensuring Excellence: Quality Assessment of English Text and Speech Data Using NLP and ML
Keywords:
ML, NLP, English Learning System, Quality Assurance, Speech to text ConverterAbstract
The effectiveness and precision of speech processing and natural language processing (NLP) applications are substantially influenced by the quality of text and speech input. The combination of NLP and Machine Learning (ML) techniques has shown tremendous promise in recent years for improving the quality of written and verbal data. The present research enables a thorough investigation of techniques and strategies to enhance data quality using NLP and ML. The results discussed in this research provide useful insights into cutting-edge methods for combining NLP and ML to assess the quality of English data. The study promotes the reliability and efficacy of English data for various kinds of NLP and ML applications, such as sentiment analysis, information retrieval, and text categorization, and provides the foundation for additional research in this area.
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