b'Zhijian Ou'

research

∙ 09/20/2023

UniPCM: Universal Pre-trained Conversation Model with Task-aware Automatic Prompt

Recent research has shown that multi-task pre-training greatly improves ...

0 Yucheng Cai, et al. ∙

research

∙ 05/22/2023

Knowledge-Retrieval Task-Oriented Dialog Systems with Semi-Supervision

Most existing task-oriented dialog (TOD) systems track dialog states in ...

0 Yucheng Cai, et al. ∙

research

∙ 05/22/2023

Exploring Energy-based Language Models with Different Architectures and Training Methods for Speech Recognition

Energy-based language models (ELMs) parameterize an unnormalized distrib...

0 Hong Liu, et al. ∙

research

∙ 04/21/2023

Persistently Trained, Diffusion-assisted Energy-based Models

Maximum likelihood (ML) learning for energy-based models (EBMs) is chall...

0 Xinwei Zhang, et al. ∙

research

∙ 10/17/2022

A Generative User Simulator with GPT-based Architecture and Goal State Tracking for Reinforced Multi-Domain Dialog Systems

Building user simulators (USs) for reinforcement learning (RL) of task-o...

0 Hong Liu, et al. ∙

research

∙ 10/13/2022

Jointly Reinforced User Simulator and Task-oriented Dialog System with Simplified Generative Architecture

Recently, there has been progress in supervised funetuning pretrained GP...

0 Hong Liu, et al. ∙

research

∙ 09/27/2022

Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset

Recently, there have merged a class of task-oriented dialogue (TOD) data...

0 Hong Liu, et al. ∙

research

∙ 07/25/2022

Advancing Semi-Supervised Task Oriented Dialog Systems by JSA Learning of Discrete Latent Variable Models

Developing semi-supervised task-oriented dialog (TOD) systems by leverag...

0 Yucheng Cai, et al. ∙

research

∙ 07/06/2022

A Challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems

A challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Syste...

0 Zhijian Ou, et al. ∙

research

∙ 04/13/2022

Revisiting Markovian Generative Architectures for Efficient Task-Oriented Dialog Systems

Recently, Transformer based pretrained language models (PLMs), such as G...

0 Hong Liu, et al. ∙

research

∙ 03/31/2022

An Empirical Study of Language Model Integration for Transducer based Speech Recognition

Utilizing text-only data with an external language model (LM) in end-to-...

0 Huahuan Zheng, et al. ∙

research

∙ 03/31/2022

CUSIDE: Chunking, Simulating Future Context and Decoding for Streaming ASR

History and future contextual information are known to be important for ...

0 Keyu An, et al. ∙

research

∙ 03/31/2022

Exploiting Single-Channel Speech for Multi-Channel End-to-End Speech Recognition: A Comparative Study

Recently, the end-to-end training approach for multi-channel ASR has sho...

0 Keyu An, et al. ∙

research

∙ 11/02/2021

iCallee: Recovering Call Graphs for Binaries

Recovering programs' call graphs is crucial for inter-procedural analysi...

0 Wenyu Zhu, et al. ∙

research

∙ 09/09/2021

Variational Latent-State GPT for Semi-supervised Task-Oriented Dialog Systems

Recently, two approaches, fine-tuning large pre-trained language models ...

0 Hong Liu, et al. ∙

research

∙ 07/11/2021

Multilingual and crosslingual speech recognition using phonological-vector based phone embeddings

The use of phonological features (PFs) potentially allows language-speci...

0 Chengrui Zhu, et al. ∙

research

∙ 07/07/2021

Advancing CTC-CRF Based End-to-End Speech Recognition with Wordpieces and Conformers

Automatic speech recognition systems have been largely improved in the p...

0 Huahuan Zheng, et al. ∙

research

∙ 04/30/2021

Deformable TDNN with adaptive receptive fields for speech recognition

Time Delay Neural Networks (TDNNs) are widely used in both DNN-HMM based...

0 Keyu An, et al. ∙

research

∙ 11/13/2020

The SLT 2021 children speech recognition challenge: Open datasets, rules and baselines

Automatic speech recognition (ASR) has been significantly advanced with ...

0 Fan Yu, et al. ∙

research

∙ 11/11/2020

Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through Gradients

Neural Architecture Search (NAS), the process of automating architecture...

0 Huahuan Zheng, et al. ∙

research

∙ 10/25/2020

An empirical study of domain-agnostic semi-supervised learning via energy-based models: joint-training and pre-training

A class of recent semi-supervised learning (SSL) methods heavily rely on...

0 Yunfu Song, et al. ∙

research

∙ 09/17/2020

A Probabilistic End-To-End Task-Oriented Dialog Model with Latent Belief States towards Semi-Supervised Learning

Structured belief states are crucial for user goal tracking and database...

0 Yichi Zhang, et al. ∙

research

∙ 05/28/2020

Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models

Although with progress in introducing auxiliary amortized inference mode...

0 Zhijian Ou, et al. ∙

research

∙ 05/27/2020

CAT: A CTC-CRF based ASR Toolkit Bridging the Hybrid and the End-to-end Approaches towards Data Efficiency and Low Latency

In this paper, we present a new open source toolkit for speech recogniti...

0 Keyu An, et al. ∙

research

∙ 04/16/2020

Paraphrase Augmented Task-Oriented Dialog Generation

Neural generative models have achieved promising performance on dialog g...

1 Silin Gao, et al. ∙

research

∙ 02/14/2020

Integrating Discrete and Neural Features via Mixed-feature Trans-dimensional Random Field Language Models

There has been a long recognition that discrete features (n-gram feature...

0 Silin Gao, et al. ∙

research

∙ 11/24/2019

Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context

Conversations have an intrinsic one-to-many property, which means that m...

0 Yichi Zhang, et al. ∙

research

∙ 11/20/2019

CAT: CRF-based ASR Toolkit

In this paper, we present a new open source toolkit for automatic speech...

0 Keyu An, et al. ∙

research

∙ 11/04/2018

Neural CRF transducers for sequence labeling

Conditional random fields (CRFs) have been shown to be one of the most s...

0 Kai Hu, et al. ∙

research

∙ 11/04/2018

Elastic CRFs for Open-ontology Slot Filling

Slot filling is a crucial component in task-oriented dialog systems, whi...

0 Yinpei Dai, et al. ∙

research

∙ 08/05/2018

A Review of Learning with Deep Generative Models from perspective of graphical modeling

This document aims to provide a review on learning with deep generative ...

0 Zhijian Ou, et al. ∙

research

∙ 07/13/2018

Hybrid CTC-Attention based End-to-End Speech Recognition using Subword Units

In this paper, we present an end-to-end automatic speech recognition sys...

0 Zhangyu Xiao, et al. ∙

research

∙ 07/03/2018

Improved training of neural trans-dimensional random field language models with dynamic noise-contrastive estimation

A new whole-sentence language model - neural trans-dimensional random fi...

0 Bin Wang, et al. ∙

research

∙ 06/01/2018

Learning Neural Random Fields with Inclusive Auxiliary Generators

In this paper we develop Neural Random Field learning with Inclusive-div...

0 Yunfu Song, et al. ∙

research

∙ 03/01/2018

Learning Sparse Structured Ensembles with SG-MCMC and Network Pruning

An ensemble of neural networks is known to be more robust and accurate t...

0 Yichi Zhang, et al. ∙

research

∙ 11/09/2017

Tracking of enriched dialog states for flexible conversational information access

Dialog state tracking (DST) is a crucial component in a task-oriented di...

0 Yinpei Dai, et al. ∙

research

∙ 10/30/2017

Learning neural trans-dimensional random field language models with noise-contrastive estimation

Trans-dimensional random field language models (TRF LMs) where sentences...

0 Bin Wang, et al. ∙

research

∙ 07/23/2017

Language modeling with Neural trans-dimensional random fields

Trans-dimensional random field language models (TRF LMs) have recently b...

0 Bin Wang, et al. ∙

research

∙ 03/30/2016

Model Interpolation with Trans-dimensional Random Field Language Models for Speech Recognition

The dominant language models (LMs) such as n-gram and neural network (NN...

0 Bin Wang, et al. ∙

research

∙ 03/20/2016

Joint Stochastic Approximation learning of Helmholtz Machines

Though with progress, model learning and performing posterior inference ...

0 Haotian Xu, et al. ∙

research

∙ 03/20/2015

Block-Wise MAP Inference for Determinantal Point Processes with Application to Change-Point Detection

Existing MAP inference algorithms for determinantal point processes (DPP...

0 Jinye Zhang, et al. ∙

Zhijian Ou

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