31 citations · 47 across the 5 of their papers we have counts for
5 papers
Disentangling speech from surroundings with neural embeddings
Ahmed Omran, Neil Zeghidour, Zalán Borsos +3
We present a method to separate speech signals from noisy environments in the embedding space of a neural audio codec. We introduce a new training procedure that allows our model t…
Multi-Channel Speech Denoising for Machine Ears
Cong Han, E. Merve Kaya, Kyle Hoefer +2
This work describes a speech denoising system for machine ears that aims to improve speech intelligibility and the overall listening experience in noisy environments. We recorded a…
Neural Architecture Search for Energy Efficient Always-on Audio Models
Daniel T. Speckhard, Karolis Misiunas, Sagi Perel +3
Mobile and edge computing devices for always-on classification tasks require energy-efficient neural network architectures. In this paper we present several changes to neural archi…
Putting a Face to the Voice: Fusing Audio and Visual Signals Across a Video to Determine Speakers
Ken Hoover, Sourish Chaudhuri, Caroline Pantofaru +2
In this paper, we present a system that associates faces with voices in a video by fusing information from the audio and visual signals. The thesis underlying our work is that an e…
CNN Architectures for Large-Scale Audio Classification
Shawn Hershey, Sourish Chaudhuri, Daniel P. W. Ellis +10
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of…