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Automatic Speech Recognition

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Showing 2476–2500 of 3174 papers

TitleStatusHype
Dynamic Masking for Improved Stability in Spoken Language Translation—0
An Audio-enriched BERT-based Framework for Spoken Multiple-choice Question Answering—0
FT Speech: Danish Parliament Speech Corpus—0
An End-to-End Mispronunciation Detection System for L2 English Speech Leveraging Novel Anti-Phone Modeling—0
Detecting Adversarial Examples for Speech Recognition via Uncertainty QuantificationCode0
Large scale evaluation of importance maps in automatic speech recognition—0
A Comparison of Label-Synchronous and Frame-Synchronous End-to-End Models for Speech Recognition—0
Investigation of Large-Margin Softmax in Neural Language Modeling—0
Early Stage LM Integration Using Local and Global Log-Linear Combination—0
Iterative Pseudo-Labeling for Speech RecognitionCode0
Improving Proper Noun Recognition in End-to-End ASR By Customization of the MWER Loss Criterion—0
A systematic comparison of grapheme-based vs. phoneme-based label units for encoder-decoder-attention models—0
Generative Adversarial Training Data Adaptation for Very Low-resource Automatic Speech RecognitionCode0
Quaternion Neural Networks for Multi-channel Distant Speech Recognition—0
Weak-Attention Suppression For Transformer Based Speech Recognition—0
Audio-visual Multi-channel Recognition of Overlapped Speech—0
An Effective End-to-End Modeling Approach for Mispronunciation Detection—0
That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages—0
Reducing Spelling Inconsistencies in Code-Switching ASR using Contextualized CTC Loss—0
Dynamic Sparsity Neural Networks for Automatic Speech Recognition—0
AccentDB: A Database of Non-Native English Accents to Assist Neural Speech Recognition—0
Context-Dependent Acoustic Modeling without Explicit Phone Clustering—0
Contextualizing ASR Lattice Rescoring with Hybrid Pointer Network Language Model—0
You Do Not Need More Data: Improving End-To-End Speech Recognition by Text-To-Speech Data Augmentation—0
Coupled Training of Sequence-to-Sequence Models for Accented Speech RecognitionCode0
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