3 citations · 3 across the 7 of their papers we have counts for
7 papers
Re-ENACT: Reinforcement Learning for Emotional Speech Generation using Actor-Critic Strategy
Ravi Shankar, Archana Venkataraman
In this paper, we propose the first method to modify the prosodic features of a given speech signal using actor-critic reinforcement learning strategy. Our approach uses a Bayesian…
A Closer Look at Wav2Vec2 Embeddings for On-Device Single-Channel Speech Enhancement
Ravi Shankar, Ke Tan, Buye Xu +1
Self-supervised learned models have been found to be very effective for certain speech tasks such as automatic speech recognition, speaker identification, keyword spotting and othe…
A Diffeomorphic Flow-based Variational Framework for Multi-speaker Emotion Conversion
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon +1
This paper introduces a new framework for non-parallel emotion conversion in speech. Our framework is based on two key contributions. First, we propose a stochastic version of the…
A Comparative Study of Data Augmentation Techniques for Deep Learning Based Emotion Recognition
Ravi Shankar, Abdouh Harouna Kenfack, Arjun Somayazulu +1
Automated emotion recognition in speech is a long-standing problem. While early work on emotion recognition relied on hand-crafted features and simple classifiers, the field has no…
A Deep-Bayesian Framework for Adaptive Speech Duration Modification
Ravi Shankar, Archana Venkataraman
We propose the first method to adaptively modify the duration of a given speech signal. Our approach uses a Bayesian framework to define a latent attention map that links frames of…
Multi-speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network
Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon +1
We propose a novel method for emotion conversion in speech based on a chained encoder-decoder-predictor neural network architecture. The encoder constructs a latent embedding of th…
Non-parallel Emotion Conversion using a Deep-Generative Hybrid Network and an Adversarial Pair Discriminator
Ravi Shankar, Jacob Sager, Archana Venkataraman
We introduce a novel method for emotion conversion in speech that does not require parallel training data. Our approach loosely relies on a cycle-GAN schema to minimize the reconst…