Sri Karlapati

According to our database1, Sri Karlapati authored at least 16 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
BASE TTS: Lessons from building a billion-parameter Text-to-Speech model on 100K hours of data.
CoRR, 2024

Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials.
CoRR, 2024

2023
A Comparative Analysis of Pretrained Language Models for Text-to-Speech.
CoRR, 2023

eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody Transfer.
CoRR, 2023

2022
Simple and Effective Multi-sentence TTS with Expressive and Coherent Prosody.
CoRR, 2022

Expressive, Variable, and Controllable Duration Modelling in TTS.
CoRR, 2022

CopyCat2: A Single Model for Multi-Speaker TTS and Many-to-Many Fine-Grained Prosody Transfer.
CoRR, 2022

Simple and Effective Multi-sentence TTS with Expressive and Coherent Prosody.
Proceedings of the Interspeech 2022, 2022

CopyCat2: A Single Model for Multi-Speaker TTS and Many-to-Many Fine-Grained Prosody Transfer.
Proceedings of the Interspeech 2022, 2022

Expressive, Variable, and Controllable Duration Modelling in TTS.
Proceedings of the Interspeech 2022, 2022

2021
Multi-Scale Spectrogram Modelling for Neural Text-to-Speech.
CoRR, 2021

Voicy: Zero-Shot Non-Parallel Voice Conversion in Noisy Reverberant Environments.
CoRR, 2021

A Learned Conditional Prior for the VAE Acoustic Space of a TTS System.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech.
Proceedings of the IEEE International Conference on Acoustics, 2021

Camp: A Two-Stage Approach to Modelling Prosody in Context.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
CopyCat: Many-to-Many Fine-Grained Prosody Transfer for Neural Text-to-Speech.
Proceedings of the Interspeech 2020, 2020


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