b'Weiran Wang'

research

∙ 03/31/2023

Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR

Conformer models maintain a large number of internal states, the vast ma...

0 Rami Botros, et al. ∙

research

∙ 02/16/2023

JEIT: Joint End-to-End Model and Internal Language Model Training for Speech Recognition

We propose JEIT, a joint end-to-end (E2E) model and internal language mo...

0 Zhong Meng, et al. ∙

research

∙ 10/13/2022

JOIST: A Joint Speech and Text Streaming Model For ASR

We present JOIST, an algorithm to train a streaming, cascaded, encoder e...

0 Tara N. Sainath, et al. ∙

research

∙ 06/29/2022

Improving Deliberation by Text-Only and Semi-Supervised Training

Text-only and semi-supervised training based on audio-only data has gain...

0 Ke Hu, et al. ∙

research

∙ 04/15/2022

Streaming Align-Refine for Non-autoregressive Deliberation

We propose a streaming non-autoregressive (non-AR) decoding algorithm to...

0 Weiran Wang, et al. ∙

research

∙ 04/15/2022

Improving Rare Word Recognition with LM-aware MWER Training

Language models (LMs) significantly improve the recognition accuracy of ...

0 Weiran Wang, et al. ∙

research

∙ 04/13/2022

A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes

In this paper, we propose a dynamic cascaded encoder Automatic Speech Re...

0 Shaojin Ding, et al. ∙

research

∙ 10/22/2021

Contrastively Disentangled Sequential Variational Autoencoder

Self-supervised disentangled representation learning is a critical task ...

16 Junwen Bai, et al. ∙

research

∙ 06/14/2021

Latent Correlation-Based Multiview Learning and Self-Supervision: A Unifying Perspective

Multiple views of data, both naturally acquired (e.g., image and audio) ...

0 Qi Lyu, et al. ∙

research

∙ 10/07/2020

Representation Learning for Sequence Data with Deep Autoencoding Predictive Components

We propose Deep Autoencoding Predictive Components (DAPC) – a self-super...

0 Junwen Bai, et al. ∙

research

∙ 02/14/2020

A Comparison of Pooling Methods on LSTM Models for Rare Acoustic Event Classification

Acoustic event classification (AEC) and acoustic event detection (AED) r...

0 Chieh-Chi Kao, et al. ∙

research

∙ 01/28/2020

Unsupervised Pre-training of Bidirectional Speech Encoders via Masked Reconstruction

We propose an approach for pre-training speech representations via a mas...

0 Weiran Wang, et al. ∙

research

∙ 01/24/2020

Data Techniques For Online End-to-end Speech Recognition

Practitioners often need to build ASR systems for new use cases in a sho...

0 Yang Chen, et al. ∙

research

∙ 01/24/2020

Semi-supervised ASR by End-to-end Self-training

While deep learning based end-to-end automatic speech recognition (ASR) ...

0 Yang Chen, et al. ∙

research

∙ 09/16/2019

Acoustic scene analysis with multi-head attention networks

Acoustic Scene Classification (ASC) is a challenging task, as a single s...

9 Weimin Wang, et al. ∙

research

∙ 06/24/2019

Multimodal and Multi-view Models for Emotion Recognition

Studies on emotion recognition (ER) show that combining lexical and acou...

0 Gustavo Aguilar, et al. ∙

research

∙ 03/08/2019

Everything old is new again: A multi-view learning approach to learning using privileged information and distillation

We adopt a multi-view approach for analyzing two knowledge transfer sett...

0 Weiran Wang, et al. ∙

research

∙ 08/20/2018

A simple model for detection of rare sound events

We propose a simple recurrent model for detecting rare sound events, whe...

0 Weiran Wang, et al. ∙

research

∙ 08/20/2018

R-CRNN: Region-based Convolutional Recurrent Neural Network for Audio Event Detection

This paper proposes a Region-based Convolutional Recurrent Neural Networ...

0 Chieh-Chi Kao, et al. ∙

research

∙ 03/19/2018

Acoustic feature learning using cross-domain articulatory measurements

Previous work has shown that it is possible to improve speech recognitio...

0 Qingming Tang, et al. ∙

research

∙ 03/19/2018

Acoustic feature learning cross-domain articulatory measurements

Previous work has shown that it is possible to improve speech recognitio...

0 Qingming Tang, et al. ∙

research

∙ 02/11/2018

Distributed Stochastic Multi-Task Learning with Graph Regularization

We propose methods for distributed graph-based multi-task learning that ...

0 Weiran Wang, et al. ∙

research

∙ 08/11/2017

Acoustic Feature Learning via Deep Variational Canonical Correlation Analysis

We study the problem of acoustic feature learning in the setting where w...

0 Qingming Tang, et al. ∙

research

∙ 02/25/2017

Efficient coordinate-wise leading eigenvector computation

We develop and analyze efficient "coordinate-wise" methods for finding t...

0 Jialei Wang, et al. ∙

research

∙ 02/21/2017

Stochastic Canonical Correlation Analysis

We tightly analyze the sample complexity of CCA, provide a learning algo...

0 Chao Gao, et al. ∙

research

∙ 11/14/2016

Multi-view Recurrent Neural Acoustic Word Embeddings

Recent work has begun exploring neural acoustic word embeddings---fixed-...

0 Wanjia He, et al. ∙

research

∙ 10/21/2016

End-to-End Training Approaches for Discriminative Segmental Models

Recent work on discriminative segmental models has shown that they can a...

0 Hao Tang, et al. ∙

research

∙ 09/26/2016

Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation

We study the problem of recognizing video sequences of fingerspelled let...

0 Taehwan Kim, et al. ∙

research

∙ 08/02/2016

Efficient Segmental Cascades for Speech Recognition

Discriminative segmental models offer a way to incorporate flexible feat...

0 Hao Tang, et al. ∙

research

∙ 02/13/2016

Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation

We study the problem of recognition of fingerspelled letter sequences in...

0 Taehwan Kim, et al. ∙

research

∙ 02/07/2016

Network Inference by Learned Node-Specific Degree Prior

We propose a novel method for network inference from partially observed ...

0 Qingming Tang, et al. ∙

research

∙ 02/05/2016

On Column Selection in Approximate Kernel Canonical Correlation Analysis

We study the problem of column selection in large-scale kernel canonical...

0 Weiran Wang, et al. ∙

research

∙ 11/16/2015

Nonparametric Canonical Correlation Analysis

Canonical correlation analysis (CCA) is a classical representation learn...

0 Tomer Michaeli, et al. ∙

research

∙ 10/05/2015

Deep convolutional acoustic word embeddings using word-pair side information

Recent studies have been revisiting whole words as the basic modelling u...

0 Herman Kamper, et al. ∙

research

∙ 07/22/2015

Discriminative Segmental Cascades for Feature-Rich Phone Recognition

Discriminative segmental models, such as segmental conditional random fi...

0 Hao Tang, et al. ∙

research

∙ 05/26/2014

The role of dimensionality reduction in linear classification

Dimensionality reduction (DR) is often used as a preprocessing step in c...

0 Weiran Wang, et al. ∙

research

∙ 05/23/2014

LASS: a simple assignment model with Laplacian smoothing

We consider the problem of learning soft assignments of N items to K cat...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

research

∙ 09/06/2013

Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application

We provide an elementary proof of a simple, efficient algorithm for comp...

0 Weiran Wang, et al. ∙

research

∙ 04/24/2013

The K-modes algorithm for clustering

Many clustering algorithms exist that estimate a cluster centroid, such ...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

research

∙ 12/24/2012

Distributed optimization of deeply nested systems

In science and engineering, intelligent processing of complex signals su...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

Weiran Wang

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