40 citations · 229 across the 25 of their papers we have counts for
25 papers
On the Transferability of Whisper-based Representations for "In-the-Wild" Cross-Task Downstream Speech Applications
Vamsikrishna Chemudupati, Marzieh Tahaei, Heitor Guimaraes +5
Large self-supervised pre-trained speech models have achieved remarkable success across various speech-processing tasks. The self-supervised training of these models leads to unive…
Mathematical Challenges in Deep Learning
Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev +8
Deep models are dominating the artificial intelligence (AI) industry since the ImageNet challenge in 2012. The size of deep models is increasing ever since, which brings new challe…
Adapting Offline Speech Translation Models for Streaming with Future-Aware Distillation and Inference
Biao Fu, Minpeng Liao, Kai Fan +4
A popular approach to streaming speech translation is to employ a single offline model with a wait-k policy to support different latency requirements, which is simpler than trainin…
RobustDistiller: Compressing Universal Speech Representations for Enhanced Environment Robustness
Heitor R. Guimarães, Arthur Pimentel, Anderson R. Avila +3
Self-supervised speech pre-training enables deep neural network models to capture meaningful and disentangled factors from raw waveform signals. The learned universal speech repres…
Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation
Chen Wang, Yuchen Liu, Boxing Chen +4
End-to-end Speech Translation (ST) aims at translating the source language speech into target language text without generating the intermediate transcriptions. However, the trainin…
Efficient Cluster-Based k-Nearest-Neighbor Machine Translation
Dexin Wang, Kai Fan, Boxing Chen +1
k-Nearest-Neighbor Machine Translation (kNN-MT) has been recently proposed as a non-parametric solution for domain adaptation in neural machine translation (NMT). It aims to allevi…