research
∙
08/11/2023
Improving Joint Speech-Text Representations Without Alignment
The last year has seen astonishing progress in text-prompted image gener...
share
research
∙
04/19/2023
A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale
Unpaired text and audio injection have emerged as dominant methods for i...
research
∙
01/11/2023
Dual Learning for Large Vocabulary On-Device ASR
Dual learning is a paradigm for semi-supervised machine learning that se...
research
∙
08/28/2022
Towards Disentangled Speech Representations
The careful construction of audio representations has become a dominant ...
research
∙
11/18/2021
Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions
It is well known that many machine learning systems demonstrate bias tow...
research
∙
11/08/2021
Cascaded Multilingual Audio-Visual Learning from Videos
In this paper, we explore self-supervised audio-visual models that learn...
research
∙
04/26/2021
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos
Multimodal self-supervised learning is getting more and more attention a...
research
∙
04/09/2021
Accented Speech Recognition Inspired by Human Perception
While improvements have been made in automatic speech recognition perfor...
research
∙
04/07/2021
Speak or Chat with Me: End-to-End Spoken Language Understanding System with Flexible Inputs
A major focus of recent research in spoken language understanding (SLU) ...
research
∙
04/03/2021
Diarization of Legal Proceedings. Identifying and Transcribing Judicial Speech from Recorded Court Audio
United States Courts make audio recordings of oral arguments available a...
research
∙
10/08/2020
Leveraging Unpaired Text Data for Training End-to-End Speech-to-Intent Systems
Training an end-to-end (E2E) neural network speech-to-intent (S2I) syste...
research
∙
06/16/2020
AVLnet: Learning Audio-Visual Language Representations from Instructional Videos
Current methods for learning visually grounded language from videos ofte...
research
∙
02/24/2020
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition
The past decade has witnessed great progress in Automatic Speech Recogni...
research
∙
02/04/2020
Improving Efficiency in Large-Scale Decentralized Distributed Training
Decentralized Parallel SGD (D-PSGD) and its asynchronous variant Asynchr...
research
∙
09/29/2019
Identifying Mood Episodes Using Dialogue Features from Clinical Interviews
Bipolar disorder, a severe chronic mental illness characterized by patho...
research
∙
08/09/2019
Challenging the Boundaries of Speech Recognition: The MALACH Corpus
There has been huge progress in speech recognition over the last several...
research
∙
07/10/2019
Large-Scale Mixed-Bandwidth Deep Neural Network Acoustic Modeling for Automatic Speech Recognition
In automatic speech recognition (ASR), wideband (WB) and narrowband (NB)...
research
∙
07/10/2019
Acoustic Model Optimization Based On Evolutionary Stochastic Gradient Descent with Anchors for Automatic Speech Recognition
Evolutionary stochastic gradient descent (ESGD) was proposed as a popula...
research
∙
07/10/2019
A Highly Efficient Distributed Deep Learning System For Automatic Speech Recognition
Modern Automatic Speech Recognition (ASR) systems rely on distributed de...
research
∙
04/30/2019
English Broadcast News Speech Recognition by Humans and Machines
With recent advances in deep learning, considerable attention has been g...
research
∙
04/10/2019
Distributed Deep Learning Strategies For Automatic Speech Recognition
In this paper, we propose and investigate a variety of distributed deep ...
research
∙
03/29/2019
Acoustically Grounded Word Embeddings for Improved Acoustics-to-Word Speech Recognition
Direct acoustics-to-word (A2W) systems for end-to-end automatic speech r...
research
∙
10/16/2018
Evolutionary Stochastic Gradient Descent for Optimization of Deep Neural Networks
We propose a population-based Evolutionary Stochastic Gradient Descent (...
research
∙
12/08/2017
Building competitive direct acoustics-to-word models for English conversational speech recognition
Direct acoustics-to-word (A2W) models in the end-to-end paradigm have re...
research
∙
03/22/2017
Direct Acoustics-to-Word Models for English Conversational Speech Recognition
Recent work on end-to-end automatic speech recognition (ASR) has shown t...
research
∙
03/06/2017
English Conversational Telephone Speech Recognition by Humans and Machines
One of the most difficult speech recognition tasks is accurate recogniti...
research
∙
01/13/2017
Kernel Approximation Methods for Speech Recognition
We study large-scale kernel methods for acoustic modeling in speech reco...
research
∙
03/18/2016
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
We study large-scale kernel methods for acoustic modeling and compare to...
research
∙
11/14/2014