Authors : Hemant Singh; Diksha Kumari; Suriya Srinija; Shree Bejon Sarkar Bappy

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://rb.gy/05bvdi

Scribd : https://tinyurl.com/y4pwzhp9

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG373

Abstract : BING_GPT is a voice assistant designed to improve the interaction of users with voice assistance. It delivers the most accurate and noiseless experience utilizing the best in language and machine learning to comprehend and respond to the inquiries of people. The technical architecture of the Bing GPT Voice Assistant is covered in this paper, along with the data processing pipelines, voice recognition technology integration, and underlying machine learning models. It also examines the difficulties encountered in the development process, including protecting user privacy, responding to a variety of user inquiries, and preserving conversational context over lengthy exchanges. The work also aims to study and comprehend the design procedure, effectiveness and efficiency, which aids in the progression of audio technology. Voice technology users get theadvantage of voice assistance because the work helps in the process’s continuation by enabling readers to know the design and working.

Keywords : Generative Pre-Trained Transformers (GPT), Voice Assistant, Natural Language Processing (NLP), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Recurrent NeuralNetwork (RNN).

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