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07/23/2023
On the Effectiveness of Offline RL for Dialogue Response Generation
A common training technique for language models is teacher forcing (TF)....
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05/18/2023
A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Tasks
Conformer, a convolution-augmented Transformer variant, has become the d...
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02/27/2023
Structured Pruning of Self-Supervised Pre-trained Models for Speech Recognition and Understanding
Self-supervised speech representation learning (SSL) has shown to be eff...
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12/20/2022
SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Tasks
Spoken language understanding (SLU) tasks have been studied for many dec...
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12/16/2022
Context-aware Fine-tuning of Self-supervised Speech Models
Self-supervised pre-trained transformers have improved the state of the ...
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09/30/2022
E-Branchformer: Branchformer with Enhanced merging for speech recognition
Conformer, combining convolution and self-attention sequentially to capt...
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05/02/2022
Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages
We introduce Wav2Seq, the first self-supervised approach to pre-train bo...
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12/14/2021
On the Use of External Data for Spoken Named Entity Recognition
Spoken language understanding (SLU) tasks involve mapping from speech au...
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11/19/2021
SLUE: New Benchmark Tasks for Spoken Language Understanding Evaluation on Natural Speech
Progress in speech processing has been facilitated by shared datasets an...
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09/14/2021
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition
This paper is a study of performance-efficiency trade-offs in pre-traine...
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06/17/2021
Multi-mode Transformer Transducer with Stochastic Future Context
Automatic speech recognition (ASR) models make fewer errors when more su...
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02/09/2021
Making Paper Reviewing Robust to Bid Manipulation Attacks
Most computer science conferences rely on paper bidding to assign review...
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06/22/2020
Attention-based Quantum Tomography
With rapid progress across platforms for quantum systems, the problem of...
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06/10/2020
Revisiting Few-sample BERT Fine-tuning
We study the problem of few-sample fine-tuning of BERT contextual repres...
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02/25/2020
On Feature Normalization and Data Augmentation
Modern neural network training relies heavily on data augmentation for i...
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09/28/2019
Integrated Triaging for Fast Reading Comprehension
Although according to several benchmarks automatic machine reading compr...
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07/09/2019
Positional Normalization
A widely deployed method for reducing the training time of deep neural n...
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04/21/2019
BERTScore: Evaluating Text Generation with BERT
We propose BERTScore, an automatic evaluation metric for text generation...
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02/28/2019
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD
In this technical report, we introduce FastFusionNet, an efficient varia...
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02/19/2019
Simplifying Graph Convolutional Networks
Graph Convolutional Networks (GCNs) and their variants have experienced ...
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01/29/2019
Pay Less Attention with Lightweight and Dynamic Convolutions
Self-attention is a useful mechanism to build generative models for lang...
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10/25/2018
Attack Graph Convolutional Networks by Adding Fake Nodes
Graph convolutional networks (GCNs) have been widely used for classifyin...
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06/19/2018
An empirical study on evaluation metrics of generative adversarial networks
Evaluating generative adversarial networks (GANs) is inherently challeng...
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11/12/2017
Fast Reading Comprehension with ConvNets
State-of-the-art deep reading comprehension models are dominated by recu...
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09/06/2017