UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 7 Issue 5
May-2020
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRDV06008


Registration ID:
231872

Page Number

25-29

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Title

Anyone GAN Sing

Abstract

The problem of audio synthesis has been increas- ingly solved using deep neural networks. With the introduction of Generative Adversarial Networks (GAN), another efficient and adjective path has opened up to solve this problem. In this paper, we present a method to synthesize the singing voice of a person using a Convolutional Long Short-term Memory (ConvLSTM) based GAN optimized using the Wasserstein loss function. Our work is inspired by WGANSing by Chandna et al. Our model inputs consecutive frame-wise linguistic and frequency features, along with singer identity and outputs vocoder features. We train the model on a dataset of 48 English songs sung and spoken by 12 non-professional singers. For inference, sequential blocks are concatenated using an overlap-add procedure. We test the model using the Mel-Cepstral Distance metric and a subjective listening test with 18 participants.

Key Words

Generative Adversarial Networks, Wasserstein- GAN, Convolutional-LSTM, Singing Voice Synthesis.

Cite This Article

"Anyone GAN Sing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.25-29, May-2020, Available :http://www.jetir.org/papers/JETIRDV06008.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Anyone GAN Sing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp25-29, May-2020, Available at : http://www.jetir.org/papers/JETIRDV06008.pdf

Publication Details

Published Paper ID: JETIRDV06008
Registration ID: 231872
Published In: Volume 7 | Issue 5 | Year May-2020
DOI (Digital Object Identifier):
Page No: 25-29
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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