3 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CL2020★ 3 cited
Multilingual Jointly Trained Acoustic and Written Word Embeddings
Yushi Hu, Shane Settle, Karen Livescu
Acoustic word embeddings (AWEs) are vector representations of spoken word segments. AWEs can be learned jointly with embeddings of character sequences, to generate phonetically mea…
cs.CL2019★ 1 cited
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition
Shane Settle, Kartik Audhkhasi, Karen Livescu +1
Direct acoustics-to-word (A2W) systems for end-to-end automatic speech recognition are simpler to train, and more efficient to decode with, than sub-word systems. However, A2W syst…
cs.CL2017
Query-by-Example Search with Discriminative Neural Acoustic Word Embeddings
Shane Settle, Keith Levin, Herman Kamper +1
Query-by-example search often uses dynamic time warping (DTW) for comparing queries and proposed matching segments. Recent work has shown that comparing speech segments by represen…