activity
20192023
most citedTie Your Embeddings Down: Cross-Modal Latent Spaces for End-to-end Spoken Language Understanding

8 citations · 15 across the 17 of their papers we have counts for

collaborators
Showing 2019Show all

1 paper · 1 filter

cs.SD2019

Speech Separation Using Gain-Adapted Factorial Hidden Markov Models

Martin H. Radfar, Richard M. Dansereau, Willy Wong

We present a new probabilistic graphical model which generalizes factorial hidden Markov models (FHMM) for the problem of single-channel speech separation (SCSS) in which we wish t…