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Found 8 papers, 1 papers with code
Fast and small footprint Hybrid HMM-HiFiGAN based system for speech synthesis in Indian languages
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.
HMM-based data augmentation for E2E systems for building conversational speech synthesis systems
This paper proposes an approach to build a high-quality text-to-speech (TTS) system for technical domains using data augmentation.
Front-end Diarization for Percussion Separation in Taniavartanam of Carnatic Music Concerts
In this work, we address the problem of separating the percussive voices in the taniavartanam segments of Carnatic music.
Towards Zero-Shot Learning with Fewer Seen Class Examples
We present a meta-learning based generative model for zero-shot learning (ZSL) towards a challenging setting when the number of training examples from each \emph{seen} class is very few.
Evidence of Task-Independent Person-Specific Signatures in EEG using Subspace Techniques
These high dimensional statistics are then projected to a lower dimensional space where the biometric information is preserved.
Stacked Adversarial Network for Zero-Shot Sketch based Image Retrieval
Conventional approaches to Sketch-Based Image Retrieval (SBIR) assume that the data of all the classes are available during training.
Spoof detection using time-delay shallow neural network and feature switching
When combined with the decision-level feature switching (DLFS) paradigm, the best TD-SNN system outperforms the best baseline GMM system on evaluation data with a relative improvement of 48. 03\% and 49. 47\% for both logical and physical access, respectively.
A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders
By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes.
