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  Published Paper Details:

  Paper Title

VOICE BASED SERVICES USING AUDIO CLASSIFICATION

  Authors

  Jay Prakash Malviya,  Dr. Shamshekhar S. Patil

  Keywords

Audio classification, Voice-based services, Voice recognition, Speaker identification, Natural language processing, Speech recognition, Language translation, Machine learning, Artificial intelligence, Human-computer interaction

  Abstract


The perfect, accurate and robust detection of the audio has been widely grown as the speech technology in the area of audio researches, audio forensics, speech recognition, and so on. However, in real time, it is a challenge to deal with the massive data arriving from distributed sources. Thus, the study introduces a method that effectively deals with the data from the different sources using the audio classification method. This method uses anywhere for our general purpose projects, Voice services are rapidly gaining popularity, with the use of virtual assistants such as Siri, Alexa, and Google Assistant becoming increasingly common. These systems rely on audio classification to understand and respond to user requests. Audio classification is the process of using machine learning algorithms to classify audio data into different categories or classes. This is a crucial component of voice services, as it allows the system to understand and interpret the user's spoken words

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2212241

  Paper ID - 228805

  Page Number(s) - c282-c288

  Pubished in - Volume 10 | Issue 12 | December 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Jay Prakash Malviya,  Dr. Shamshekhar S. Patil,   "VOICE BASED SERVICES USING AUDIO CLASSIFICATION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 12, pp.c282-c288, December 2022, Available at :http://www.ijcrt.org/papers/IJCRT2212241.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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