347 citations · 684 across the 26 of their papers we have counts for
4 papers · 1 filter
Active Learning of Non-semantic Speech Tasks with Pretrained Models
Harlin Lee, Aaqib Saeed, Andrea L. Bertozzi
Pretraining neural networks with massive unlabeled datasets has become popular as it equips the deep models with a better prior to solve downstream tasks. However, this approach ge…
On Out-of-Distribution Detection for Audio with Deep Nearest Neighbors
Zaharah Bukhsh, Aaqib Saeed
Out-of-distribution (OOD) detection is concerned with identifying data points that do not belong to the same distribution as the model's training data. For the safe deployment of p…
Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource Devices
Harlin Lee, Aaqib Saeed
This work introduces BRILLsson, a novel binary neural network-based representation learning model for a broad range of non-semantic speech tasks. We train the model with knowledge…
Contrastive Learning of General-Purpose Audio Representations
Aaqib Saeed, David Grangier, Neil Zeghidour
We introduce COLA, a self-supervised pre-training approach for learning a general-purpose representation of audio. Our approach is based on contrastive learning: it learns a repres…