Search Results for author: Sudhanshu Srivastava

Found 4 papers, 1 papers with code

Fast and small footprint Hybrid HMM-HiFiGAN based system for speech synthesis in Indian languages

no code implementations13 Feb 2023 Sudhanshu Srivastava, Ishika Gupta, Anusha Prakash, Jom Kuriakose, Hema A. Murthy

Hidden-Markov-model (HMM) based text-to-speech (HTS) offers flexibility in speaking styles along with fast training and synthesis while being computationally less intense.

Speech Synthesis

Technology Pipeline for Large Scale Cross-Lingual Dubbing of Lecture Videos into Multiple Indian Languages

no code implementations1 Nov 2022 Anusha Prakash, Arun Kumar, Ashish Seth, Bhagyashree Mukherjee, Ishika Gupta, Jom Kuriakose, Jordan Fernandes, K V Vikram, Mano Ranjith Kumar M, Metilda Sagaya Mary, Mohammad Wajahat, Mohana N, Mudit Batra, Navina K, Nihal John George, Nithya Ravi, Pruthwik Mishra, Sudhanshu Srivastava, Vasista Sai Lodagala, Vandan Mujadia, Kada Sai Venkata Vineeth, Vrunda Sukhadia, Dipti Sharma, Hema Murthy, Pushpak Bhattacharya, S Umesh, Rajeev Sangal

Cross-lingual dubbing of lecture videos requires the transcription of the original audio, correction and removal of disfluencies, domain term discovery, text-to-text translation into the target language, chunking of text using target language rhythm, text-to-speech synthesis followed by isochronous lipsyncing to the original video.

Chunking Speech Synthesis +1

Deep Learning--Based Scene Simplification for Bionic Vision

1 code implementation30 Jan 2021 Nicole Han, Sudhanshu Srivastava, Aiwen Xu, Devi Klein, Michael Beyeler

Retinal degenerative diseases cause profound visual impairment in more than 10 million people worldwide, and retinal prostheses are being developed to restore vision to these individuals.

Monocular Depth Estimation Scene Understanding +1

Deep Cross-Modal Audio-Visual Generation

no code implementations26 Apr 2017 Lele Chen, Sudhanshu Srivastava, Zhiyao Duan, Chenliang Xu

Being the first to explore this new problem, we compose two new datasets with pairs of images and sounds of musical performances of different instruments.

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