4 citations · 6 across the 3 of their papers we have counts for
3 papers
eess.AS2023★ 1 cited
Towards Selection of Text-to-speech Data to Augment ASR Training
Shuo Liu, Leda Sarı, Chunyang Wu +4
This paper presents a method for selecting appropriate synthetic speech samples from a given large text-to-speech (TTS) dataset as supplementary training data for an automatic spee…
cs.CL2023★ 1 cited
Text Generation with Speech Synthesis for ASR Data Augmentation
Zhuangqun Huang, Gil Keren, Ziran Jiang +11
Aiming at reducing the reliance on expensive human annotations, data synthesis for Automatic Speech Recognition (ASR) has remained an active area of research. While prior work main…
stat.ML2016★ 4 cited
Tunable Sensitivity to Large Errors in Neural Network Training
Gil Keren, Sivan Sabato, Björn Schuller
When humans learn a new concept, they might ignore examples that they cannot make sense of at first, and only later focus on such examples, when they are more useful for learning.…