Search Results for author: Vasista Sai Lodagala

Found 4 papers, 2 papers with code

SALTTS: Leveraging Self-Supervised Speech Representations for improved Text-to-Speech Synthesis

no code implementations2 Aug 2023 Ramanan Sivaguru, Vasista Sai Lodagala, S Umesh

In the SALTTS-parallel implementation, the representations from this second encoder are used for an auxiliary reconstruction loss with the SSL features.

Decoder Self-Supervised Learning +2

data2vec-aqc: Search for the right Teaching Assistant in the Teacher-Student training setup

1 code implementation2 Nov 2022 Vasista Sai Lodagala, Sreyan Ghosh, S. Umesh

In this paper, we propose a new Self-Supervised Learning (SSL) algorithm called data2vec-aqc, for speech representation learning from unlabeled speech data.

Automatic Speech Recognition (ASR) Representation Learning +1

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

CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representations

1 code implementation5 Oct 2022 Vasista Sai Lodagala, Sreyan Ghosh, S. Umesh

While Self-Supervised Learning has helped reap the benefit of the scale from the available unlabeled data, the learning paradigms are continuously being bettered.

Automatic Speech Recognition (ASR) Clustering +2

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