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Found 8 papers, 6 papers with code
Rhythm Modeling for Voice Conversion
Voice conversion aims to transform source speech into a different target voice.
ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech
In a series of experiments, we first demonstrate the flexibility and generalizability of our model to new speakers and styles.
A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion
Specifically, we compare discrete and soft speech units as input features.
Energy Disaggregation using Variational Autoencoders
In this paper we address these issues and propose an energy disaggregation approach based on the variational autoencoders framework.
Measuring Disentanglement: A Review of Metrics
While many advances have been made to learn these representations, it is still unclear how to quantify disentanglement.
Bag-Level Aggregation for Multiple Instance Active Learning in Instance Classification Problems
In such cases, active learning (AL) can reduce labeling costs for training a classifier by querying the expert to provide the labels of most informative instances.
Multiple Instance Learning: A Survey of Problem Characteristics and Applications
Multiple instance learning (MIL) is a form of weakly supervised learning where training instances are arranged in sets, called bags, and a label is provided for the entire bag.
Feature Learning from Spectrograms for Assessment of Personality Traits
The number of features, and difficulties linked to the feature extraction process are greatly reduced as only one type of descriptors is used, for which the 6 parameters can be tuned automatically.
