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Found 7 papers, 5 papers with code
Revisiting Self-supervised Learning of Speech Representation from a Mutual Information Perspective
We use linear probes to estimate the mutual information between the target information and learned representations, showing another insight into the accessibility to the target information from speech representations.
Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models
While discrete latent variable models have had great success in self-supervised learning, most models assume that frames are independent.
Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution
Moreover, by coupling the proposed sampling method with an unconditional DM, i. e., a DM with no auxiliary inputs to its noise predictor, we can generalize it to a wide range of SR setups.
Autoregressive Co-Training for Learning Discrete Speech Representations
While several self-supervised approaches for learning discrete speech representation have been proposed, it is unclear how these seemingly similar approaches relate to each other.
SpeechBrain: A General-Purpose Speech Toolkit
SpeechBrain is an open-source and all-in-one speech toolkit.
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline Generation
To generate inspired headlines, we propose a novel framework called POpularity-Reinforced Learning for inspired Headline Generation (PORL-HG).
An Interaction-aware Attention Network for Speech Emotion Recognition in Spoken Dialogs
In this work, we propose an interaction-aware attention network (IAAN) that incorporate contextual information in the learned vocal representation through a novel attention mechanism.
