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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | REAL TIME VOICE CLONING USING DEEP LEARNING |
| Authors Name: | KARUN DATTA RAMAKUMAR , HRUTHIK B GOWDA , SHEETHAL V , SUSHMA M , DR. MADHUSUDHANA G K |
| Unique Id: | IJSDR2305206 |
| Published In: | Volume 8 Issue 5, May-2023 |
| Abstract: | Real-time voice cloning using deep learning is an emerging field that aims to clone the voice of any speaker in real-time by leveraging the power of deep learning algorithms. This technology has numerous applications in fields such as entertainment, personal assistants, and voice authentication. Real-time voice cloning systems consist of two main components, voice cloning and text-to-speech synthesis. Deep learning approaches have been proposed to solve both these tasks, with the most promising being the SV2TTS method. SV2TTS aims to clone the voice of any speaker by conditioning a pre-trained TTS model on a low-dimensional embedding derived from a speaker encoder model. This allows for zero-shot learning, reducing the requirement for high-quality multi-speaker data. In conclusion, real-time voice cloning using deep learning has the potential to revolutionize the way we interact with technology and create a more personalized experience for users. |
| Keywords: | SV2TTS , TACOTRON, VCTK, |
| Cite Article: | "REAL TIME VOICE CLONING USING DEEP LEARNING", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 5, page no.1286 - 1288, May-2023, Available :http://www.ijsdr.org/papers/IJSDR2305206.pdf |
| Downloads: | 000337074 |
| Publication Details: | Published Paper ID: IJSDR2305206 Registration ID:206428 Published In: Volume 8 Issue 5, May-2023 DOI (Digital Object Identifier): Page No: 1286 - 1288 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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