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Dvsa: A Focused and Efficient Sparse Attention Via Explicit Selection for Speech Recognition

https://doi.org/10.2139/ssrn.4877236
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s11042-023-16438-yopenalex-extracted
A comprehensive survey on automatic speech recognition using neural networks
inferredcites →https://doi.org/10.1016/j.jksuci.2023.02.007openalex-extracted
Attention-based latent features for jointly trained end-to-end automatic speech recognition with modified speech enhancement
inferredcites →https://doi.org/10.1016/j.specom.2022.02.005openalex-extracted
Unsupervised Automatic Speech Recognition: A review
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-extracted
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01270openalex-extracted
Scaling Local Self-Attention for Parameter Efficient Visual Backbones
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01742openalex-extracted
SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01814openalex-extracted
SViTT: Temporal Learning of Sparse Video-Text Transformers
inferredcites →https://doi.org/10.1109/icassp.2015.7178964openalex-extracted
Librispeech: An ASR corpus based on public domain audio books
inferredcites →https://doi.org/10.1109/icassp.2016.7472621openalex-extracted
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
inferredcites →https://doi.org/10.1109/icassp.2018.8462506openalex-extracted
Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition
inferredcites →https://doi.org/10.1109/icassp39728.2021.9414353openalex-extracted
Transformer-Based End-to-End Speech Recognition with Local Dense Synthesizer Attention
inferredcites →https://doi.org/10.1109/icassp40776.2020.9054476openalex-extracted
Streaming Automatic Speech Recognition with the Transformer Model
inferredcites →https://doi.org/10.1109/icassp48485.2024.10447827openalex-extracted
Folding Attention: Memory and Power Optimization for On-Device Transformer-Based Streaming Speech Recognition
inferredcites →https://doi.org/10.1109/icassp49357.2023.10094588openalex-extracted
Variable Attention Masking for Configurable Transformer Transducer Speech Recognition
inferredcites →https://doi.org/10.1109/icassp49357.2023.10096693openalex-extracted
Ripple Sparse Self-Attention for Monaural Speech Enhancement
inferredcites →https://doi.org/10.1109/icasspw62465.2024.10627466openalex-extracted
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification
inferredcites →https://doi.org/10.1109/jstsp.2017.2763455openalex-extracted
Hybrid CTC/Attention Architecture for End-to-End Speech Recognition
inferredcites →https://doi.org/10.1109/o-cocosda42418.2017openalex-extracted
2017 20th Conference of the Oriental Chapter of the International Coordinating Committee on Speech Databases and Speech I/O Systems and Assessment (O-COCOSDA)
inferredcites →https://doi.org/10.1109/slt48900.2021.9383521openalex-extracted
On The Usefulness of Self-Attention for Automatic Speech Recognition with Transformers
inferredcites →https://doi.org/10.1109/taslp.2023.3263789openalex-extracted
A CTC Alignment-Based Non-Autoregressive Transformer for End-to-End Automatic Speech Recognition
inferredcites →https://doi.org/10.1145/3366424.3383542openalex-extracted
VisBERT: Hidden-State Visualizations for Transformers
inferredcites →https://doi.org/10.1609/aaai.v35i12.17325openalex-extracted
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
inferredcites →https://doi.org/10.1609/aaai.v37i1.25081openalex-extracted
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.19openalex-extracted
ETC: Encoding Long and Structured Inputs in Transformers
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.232openalex-extracted
Blockwise Self-Attention for Long Document Understanding
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.49openalex-extracted
Fixed Encoder Self-Attention Patterns in Transformer-Based Machine Translation
inferredcites →https://doi.org/10.18653/v1/2023.acl-long.375openalex-extracted
What social attitudes about gender does BERT encode? Leveraging insights from psycholinguistics
inferredcites →https://doi.org/10.18653/v1/d15-1166openalex-extracted
Effective Approaches to Attention-based Neural Machine Translation
inferredcites →https://doi.org/10.18653/v1/d18-1475openalex-extracted
Modeling Localness for Self-Attention Networks
inferredcites →https://doi.org/10.18653/v1/d18-2012openalex-extracted
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
inferredcites →https://doi.org/10.18653/v1/d19-1424openalex-extracted
Visualizing and Understanding the Effectiveness of BERT
inferredcites →https://doi.org/10.18653/v1/d19-1445openalex-extracted
Revealing the Dark Secrets of BERT
inferredcites →https://doi.org/10.18653/v1/p19-1032openalex-extracted
Adaptive Attention Span in Transformers
inferredcites →https://doi.org/10.18653/v1/p19-1285openalex-extracted
Transformer-XL: Attentive Language Models beyond a Fixed-Length Context
inferredcites →https://doi.org/10.21437/interspeech.2020-2231openalex-extracted
Understanding Self-Attention of Self-Supervised Audio Transformers
inferredcites →https://doi.org/10.21437/interspeech.2020-2677openalex-extracted
Transformer with Bidirectional Decoder for Speech Recognition
inferredcites →https://doi.org/10.21437/interspeech.2021-668openalex-extracted
Lightweight Causal Transformer with Local Self-Attention for Real-Time Speech Enhancement
inferredcites →https://doi.org/10.21437/interspeech.2022-11441openalex-extracted
Attention Weight Smoothing Using Prior Distributions for Transformer-Based End-to-End ASR
inferredcites →https://doi.org/10.21437/interspeech.2022-422openalex-extracted
Similarity and Content-based Phonetic Self Attention for Speech Recognition
inferredcites →https://doi.org/10.3390/s23136056openalex-extracted
Efficient Self-Attention Model for Speech Recognition-Based Assistive Robots Control
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1602.02068openalex-extracted
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
inferredcites →https://doi.org/10.48550/arxiv.1706.03762openalex-extracted
Attention Is All You Need
inferredcites →https://doi.org/10.48550/arxiv.1711.02132openalex-extracted
Weighted Transformer Network for Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1904.10509openalex-extracted
Generating Long Sequences with Sparse Transformers
inferredcites →https://doi.org/10.48550/arxiv.1911.05507openalex-extracted
Compressive Transformers for Long-Range Sequence Modelling
inferredcites →https://doi.org/10.48550/arxiv.1912.11637openalex-extracted
Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection
inferredcites →https://doi.org/10.48550/arxiv.2001.04451openalex-extracted
Reformer: The Efficient Transformer
inferredcites →https://doi.org/10.48550/arxiv.2004.05150openalex-extracted
Longformer: The Long-Document Transformer
inferredcites →https://doi.org/10.48550/arxiv.2005.00743openalex-extracted
Synthesizer: Rethinking Self-Attention in Transformer Models
inferredcites →https://doi.org/10.48550/arxiv.2007.14062openalex-extracted
Big Bird: Transformers for Longer Sequences
inferredcites →https://doi.org/10.48550/arxiv.2106.02689openalex-extracted
RegionViT: Regional-to-Local Attention for Vision Transformers
inferredcites →https://doi.org/10.48550/arxiv.2207.02971openalex-extracted
Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding
inferredcites →https://doi.org/10.48550/arxiv.2304.12706openalex-extracted
What does BERT learn about prosody?
inferredcites →https://doi.org/10.4230/lipics.itp.2023.19openalex-snapshot
Exploiting Generative AI to Scale up Intelligent Tutoring Systems
inferredcites →https://doi.org/10.48550/arxiv.2004.08483openalex-snapshot
ETC: Encoding Long and Structured Inputs in Transformers
inferredcites →https://doi.org/10.48550/arxiv.2011.04906openalex-snapshot
On the Usefulness of Self-Attention for Automatic Speech Recognition with Transformers
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