255 citations · 649 across the 19 of their papers we have counts for
10 papers · 1 filter
Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training
Sameer Khurana, Niko Moritz, Takaaki Hori +1
The performance of automatic speech recognition (ASR) systems typically degrades significantly when the training and test data domains are mismatched. In this paper, we show that s…
Transcription Is All You Need: Learning to Separate Musical Mixtures with Score as Supervision
Yun-Ning Hung, Gordon Wichern, Jonathan Le Roux
Most music source separation systems require large collections of isolated sources for training, which can be difficult to obtain. In this work, we use musical scores, which are co…
Semi-Supervised Speech Recognition via Graph-based Temporal Classification
Niko Moritz, Takaaki Hori, Jonathan Le Roux
Semi-supervised learning has demonstrated promising results in automatic speech recognition (ASR) by self-training using a seed ASR model with pseudo-labels generated for unlabeled…
Multi-Pass Transformer for Machine Translation
Peng Gao, Chiori Hori, Shijie Geng +2
In contrast with previous approaches where information flows only towards deeper layers of a stack, we consider a multi-pass transformer (MPT) architecture in which earlier layers…
AutoClip: Adaptive Gradient Clipping for Source Separation Networks
Prem Seetharaman, Gordon Wichern, Bryan Pardo +1
Clipping the gradient is a known approach to improving gradient descent, but requires hand selection of a clipping threshold hyperparameter. We present AutoClip, a simple method fo…
Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers
Shijie Geng, Peng Gao, Moitreya Chatterjee +5
Given an input video, its associated audio, and a brief caption, the audio-visual scene aware dialog (AVSD) task requires an agent to indulge in a question-answer dialog with a hum…