Real-Time Human–Machine Interaction Through Voice Augmentation Using Artificial Intelligence-Reference-Cited by-同舟云学术

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Real-Time Human–Machine Interaction Through Voice Augmentation Using Artificial Intelligence

Published:2022-08-25 Issue: Volume: Page:147-160
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
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Author:

Sumaiya M. N.,Sreekanth B. V.,Akash U. S.,Kala Aravind Sharma,Dharanendra Gowda G. M.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-2940-3_10

Reference42 articles.

1. Kameoka H, Tanaka K, Kwaśny D, Kaneko T, Hojo N (2020) ConvS2S-VC: fully convolutional sequence-to-sequence voice conversion. In: IEEE/ACM Transactions on audio, speech, and language processing, vol 28, pp 1849–1863

2. Kong Q, Cao Y, Iqbal T, Wang Y, Wang W, Plumbley MD (2020) PANNs: large-scale pretrained audio neural networks for audio pattern recognition. In: IEEE/ACM Transactions on audio, speech, and language processing, vol 28, pp 2880–2894

3. Miao H, Cheng G, Zhang P, Yan Y (2020) Online hybrid CTC/attention end-to-end automatic speech recognition architecture. IEEE/ACM Trans Audio Speech Lang Process 28:1452–1465

4. Wang D, Chen J (2018) Supervised speech separation based on deep learning: an overview. IEEE/ACM Trans Audio Speech Lang Process 26(10):1702–1726

5. Alepis E, Patsakis C (2017) Monkey says, Monkey does: security and privacy on voice assistants. IEEE Access 5:17841–17851

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1. Age Estimation based on MFCC Speech Features and Machine Learning Algorithms;2022 IEEE International Symposium on Smart Electronic Systems (iSES);2022-12

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