1 Associate Professor, Department of Computer Science (Artificial Intelligence and Machine Learning), ACE Engineering College, Hyderabad, Telangana, India.
2 IV B. Tech students Department of Computer Science (Artificial Intelligence and Machine Learning), ACE Engineering College, Hyderabad, Telangana, India.
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(03), 1596-1601
Received on 30 January 2024; revised on 14 March 2024; accepted on 16 March 2024
The integration of cutting-edge natural language processing (NLP) technology for smooth audio-to-text conversion and summarization is examined in this survey. Utilizing Facebook’s BART model for succinct summaries and Google’s Speech-to-Text API for precise transcription. The report highlights the value of sophisticated summarization models and precise transcription. It talks about how the system can be used in a variety of fields, such as podcast and video transcript generation, automated meeting transcription and summarization, content indexing and search, and more. In addition to addressing issues like context preservation and bias reduction, the survey assesses relevant research on text generation, LSTM networks, and summarization techniques. Overall, by incorporating state-of-the-art technology, this study advances the processing of audio content and eventually makes it easier to extract valuable information.
Natural Language Processing (NLP); Generative Adversarial Networks (GANs); Text generation; Deep learning; Word embeddings; summarization methods; Automatic text summarization.
Preview Article PDF
Maheshwar Reddy V, Deepika K, Adithya Surya Prakash K and Sanathan M. A survey on audio analysis: Text characterization and summarization. World Journal of Advanced Research and Reviews, 2024, 21(3), 1596-1601. Article DOI: https://doi.org/10.30574/wjarr.2024.21.3.0789