1.3k citations · 13.3k across the 201 of their papers we have counts for
4 papers · 1 filter
Speaker-IPL: Unsupervised Learning of Speaker Characteristics with i-Vector based Pseudo-Labels
Zakaria Aldeneh, Takuya Higuchi, Jee-weon Jung +6
Iterative self-training, or iterative pseudo-labeling (IPL) -- using an improved model from the current iteration to provide pseudo-labels for the next iteration -- has proven to b…
Exploring Prediction Targets in Masked Pre-Training for Speech Foundation Models
Li-Wei Chen, Takuya Higuchi, He Bai +6
Speech foundation models, such as HuBERT and its variants, are pre-trained on large amounts of unlabeled speech data and then used for a range of downstream tasks. These models use…
Towards Automatic Assessment of Self-Supervised Speech Models using Rank
Zakaria Aldeneh, Vimal Thilak, Takuya Higuchi +2
This study explores using embedding rank as an unsupervised evaluation metric for general-purpose speech encoders trained via self-supervised learning (SSL). Traditionally, assessi…
Importance of Smoothness Induced by Optimizers in FL4ASR: Towards Understanding Federated Learning for End-to-End ASR
Sheikh Shams Azam, Tatiana Likhomanenko, Martin Pelikan +1
In this paper, we start by training End-to-End Automatic Speech Recognition (ASR) models using Federated Learning (FL) and examining the fundamental considerations that can be pivo…