{"total":151,"rows":[{"id":"2201.02184","title":"Learning Audio-Visual Speech Representation by Masked Multimodal Cluster Prediction","created":"2022-01-05","cited_by_count":287,"area":null},{"id":"2111.01690","title":"Recent Advances in End-to-End Automatic Speech Recognition","created":"2021-11-02","cited_by_count":140,"area":null},{"id":"2303.03329","title":"End-to-End Speech Recognition: A Survey","created":"2023-03-03","cited_by_count":129,"area":null},{"id":"2203.14263","title":"A General Survey on Attention Mechanisms in Deep Learning","created":"2022-03-27","cited_by_count":64,"area":null},{"id":"2104.02724","title":"Relaxing the Conditional Independence Assumption of CTC-based ASR by Conditioning on Intermediate Predictions","created":"2021-04-06","cited_by_count":61,"area":null},{"id":"2212.08055","title":"UnitY: Two-pass Direct Speech-to-speech Translation with Discrete Units","created":"2022-12-15","cited_by_count":60,"area":null},{"id":"2103.16775","title":"Attention, please! A survey of Neural Attention Models in Deep Learning","created":"2021-03-31","cited_by_count":51,"area":null},{"id":"2103.09935","title":"Advancing RNN Transducer Technology for Speech Recognition","created":"2021-03-17","cited_by_count":44,"area":null},{"id":"2201.12806","title":"Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection","created":"2022-01-30","cited_by_count":39,"area":null},{"id":"2109.07513","title":"Tied & Reduced RNN-T Decoder","created":"2021-09-15","cited_by_count":36,"area":null},{"id":"2311.11108","title":"Auxiliary Losses for Learning Generalizable Concept-based Models","created":"2023-11-18","cited_by_count":35,"area":null},{"id":"2105.02412","title":"Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer","created":"2021-05-06","cited_by_count":34,"area":null},{"id":"2109.00627","title":"Tree-constrained Pointer Generator for End-to-end Contextual Speech Recognition","created":"2021-09-01","cited_by_count":32,"area":null},{"id":"2212.07850","title":"Attention as a Guide for Simultaneous Speech Translation","created":"2022-12-15","cited_by_count":32,"area":null},{"id":"2102.07594","title":"Fast End-to-End Speech Recognition via Non-Autoregressive Models and Cross-Modal Knowledge Transferring from BERT","created":"2021-02-15","cited_by_count":31,"area":null},{"id":"2104.14297","title":"End-to-End Speech Recognition from Federated Acoustic Models","created":"2021-04-29","cited_by_count":30,"area":null},{"id":"2104.02775","title":"Looking into Your Speech: Learning Cross-modal Affinity for Audio-visual Speech Separation","created":"2021-03-25","cited_by_count":27,"area":null},{"id":"2302.06419","title":"AV-data2vec: Self-supervised Learning of Audio-Visual Speech Representations with Contextualized Target Representations","created":"2023-02-10","cited_by_count":27,"area":null},{"id":"2301.11716","title":"Pre-training for Speech Translation: CTC Meets Optimal Transport","created":"2023-01-27","cited_by_count":25,"area":null},{"id":"2112.03603","title":"Handwritten Mathematical Expression Recognition via Attention Aggregation based Bi-directional Mutual Learning","created":"2021-12-07","cited_by_count":20,"area":null},{"id":"2101.05525","title":"An evaluation of word-level confidence estimation for end-to-end automatic speech recognition","created":"2021-01-14","cited_by_count":18,"area":null},{"id":"2106.09009","title":"End-to-End Spoken Language Understanding for Generalized Voice Assistants","created":"2021-06-16","cited_by_count":17,"area":null},{"id":"2110.06841","title":"On Language Model Integration for RNN Transducer based Speech Recognition","created":"2021-10-13","cited_by_count":17,"area":null},{"id":"2210.16481","title":"Accelerating RNN-T Training and Inference Using CTC guidance","created":"2022-10-29","cited_by_count":17,"area":null},{"id":"2410.01537","title":"Attention layers provably solve single-location regression","created":"2024-10-02","cited_by_count":17,"area":null},{"id":"2211.05756","title":"Massively Multilingual ASR on 70 Languages: Tokenization, Architecture, and Generalization Capabilities","created":"2022-11-10","cited_by_count":16,"area":null},{"id":"2110.03334","title":"Knowledge Distillation for Neural Transducers from Large Self-Supervised Pre-trained Models","created":"2021-10-07","cited_by_count":15,"area":"distill"},{"id":"2204.10586","title":"Efficient Training of Neural Transducer for Speech Recognition","created":"2022-04-22","cited_by_count":14,"area":null},{"id":"2303.08648","title":"An End-to-End Multi-Task Learning Model for Image-based Table Recognition","created":"2023-03-15","cited_by_count":14,"area":null},{"id":"2101.03229","title":"Domain-aware Neural Language Models for Speech Recognition","created":"2021-01-05","cited_by_count":13,"area":null},{"id":"2210.10027","title":"Maestro-U: Leveraging joint speech-text representation learning for zero supervised speech ASR","created":"2022-10-18","cited_by_count":13,"area":null},{"id":"2102.07935","title":"Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation","created":"2021-02-16","cited_by_count":12,"area":"distill"},{"id":"2105.03010","title":"Efficient Weight factorization for Multilingual Speech Recognition","created":"2021-05-07","cited_by_count":12,"area":null},{"id":"2211.13866","title":"Minimal Width for Universal Property of Deep RNN","created":"2022-11-25","cited_by_count":12,"area":null},{"id":"2104.09106","title":"Acoustic Data-Driven Subword Modeling for End-to-End Speech Recognition","created":"2021-04-19","cited_by_count":11,"area":null},{"id":"2205.09058","title":"Minimising Biasing Word Errors for Contextual ASR with the Tree-Constrained Pointer Generator","created":"2022-05-18","cited_by_count":11,"area":null},{"id":"2102.01013","title":"End2End Acoustic to Semantic Transduction","created":"2021-02-01","cited_by_count":10,"area":null},{"id":"2205.12304","title":"Adaptive multilingual speech recognition with pretrained models","created":"2022-05-24","cited_by_count":9,"area":null},{"id":"2206.03318","title":"LegoNN: Building Modular Encoder-Decoder Models","created":"2022-06-07","cited_by_count":9,"area":null},{"id":"2409.18654","title":"Speech-Mamba: Long-Context Speech Recognition with Selective State Spaces Models","created":"2024-09-27","cited_by_count":9,"area":"ssm"},{"id":"2104.04487","title":"Language model fusion for streaming end to end speech recognition","created":"2021-04-09","cited_by_count":8,"area":null},{"id":"2207.03169","title":"End-to-end Speech-to-Punctuated-Text Recognition","created":"2022-07-07","cited_by_count":8,"area":null},{"id":"2210.07189","title":"On Compressing Sequences for Self-Supervised Speech Models","created":"2022-10-13","cited_by_count":8,"area":null},{"id":"2303.10917","title":"Knowledge Distillation from Multiple Foundation Models for End-to-End Speech Recognition","created":"2023-03-20","cited_by_count":8,"area":"distill"},{"id":"2305.12011","title":"Boosting Crop Classification by Hierarchically Fusing Satellite, Rotational, and Contextual Data","created":"2023-05-19","cited_by_count":8,"area":null},{"id":"2107.04154","title":"On lattice-free boosted MMI training of HMM and CTC-based full-context ASR models","created":"2021-07-09","cited_by_count":7,"area":null},{"id":"2202.06045","title":"USTED: Improving ASR with a Unified Speech and Text Encoder-Decoder","created":"2022-02-12","cited_by_count":7,"area":null},{"id":"2202.09003","title":"End-to-end contextual asr based on posterior distribution adaptation for hybrid ctc/attention system","created":"2022-02-18","cited_by_count":7,"area":null},{"id":"2203.12906","title":"Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks","created":"2022-03-24","cited_by_count":7,"area":null},{"id":"2204.03855","title":"Hierarchical Softmax for End-to-End Low-resource Multilingual Speech Recognition","created":"2022-04-08","cited_by_count":7,"area":null},{"id":"2211.01522","title":"Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing","created":"2022-11-02","cited_by_count":7,"area":null},{"id":"2104.00120","title":"Multi-Encoder Learning and Stream Fusion for Transformer-Based End-to-End Automatic Speech Recognition","created":"2021-03-31","cited_by_count":6,"area":null},{"id":"2104.04781","title":"Boosted Embeddings for Time Series Forecasting","created":"2021-04-10","cited_by_count":6,"area":null},{"id":"2201.01209","title":"Speech-to-SQL: Towards Speech-driven SQL Query Generation From Natural Language Question","created":"2022-01-04","cited_by_count":6,"area":null},{"id":"2207.11697","title":"Improving Mandarin Speech Recogntion with Block-augmented Transformer","created":"2022-07-24","cited_by_count":6,"area":null},{"id":"2305.18824","title":"Graph Neural Networks for Contextual ASR with the Tree-Constrained Pointer Generator","created":"2023-05-30","cited_by_count":6,"area":null},{"id":"2102.07259","title":"Thank you for Attention: A survey on Attention-based Artificial Neural Networks for Automatic Speech Recognition","created":"2021-02-14","cited_by_count":5,"area":null},{"id":"2102.08575","title":"End-to-end lyrics Recognition with Voice to Singing Style Transfer","created":"2021-02-17","cited_by_count":5,"area":null},{"id":"2201.03655","title":"A Likelihood Ratio based Domain Adaptation Method for E2E Models","created":"2022-01-10","cited_by_count":5,"area":null},{"id":"2205.09456","title":"Insights on Neural Representations for End-to-End Speech Recognition","created":"2022-05-19","cited_by_count":5,"area":null},{"id":"2206.02797","title":"FedNST: Federated Noisy Student Training for Automatic Speech Recognition","created":"2022-06-06","cited_by_count":5,"area":null},{"id":"2209.09735","title":"Relaxed Attention for Transformer Models","created":"2022-09-20","cited_by_count":5,"area":null},{"id":"2211.00174","title":"Joint Audio/Text Training for Transformer Rescorer of Streaming Speech Recognition","created":"2022-10-31","cited_by_count":5,"area":null},{"id":"2103.08086","title":"Multi-Discriminator Sobolev Defense-GAN Against Adversarial Attacks for End-to-End Speech Systems","created":"2021-03-15","cited_by_count":4,"area":null},{"id":"2106.03494","title":"Weakly-supervised word-level pronunciation error detection in non-native English speech","created":"2021-06-07","cited_by_count":4,"area":null},{"id":"2107.01549","title":"Unified Autoregressive Modeling for Joint End-to-End Multi-Talker Overlapped Speech Recognition and Speaker Attribute Estimation","created":"2021-07-04","cited_by_count":4,"area":null},{"id":"2107.01569","title":"Cross-Modal Transformer-Based Neural Correction Models for Automatic Speech Recognition","created":"2021-07-04","cited_by_count":4,"area":null},{"id":"2112.10202","title":"Integrating Knowledge in End-to-End Automatic Speech Recognition for Mandarin-English Code-Switching","created":"2021-12-19","cited_by_count":4,"area":null},{"id":"2202.13427","title":"Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory Prediction","created":"2022-02-27","cited_by_count":4,"area":null},{"id":"2205.12462","title":"Improving CTC-based ASR Models with Gated Interlayer Collaboration","created":"2022-05-25","cited_by_count":4,"area":null},{"id":"2207.00774","title":"Computer-assisted Pronunciation Training -- Speech synthesis is almost all you need","created":"2022-07-02","cited_by_count":4,"area":null},{"id":"2208.10838","title":"Multimodal Crop Type Classification Fusing Multi-Spectral Satellite Time Series with Farmers Crop Rotations and Local Crop Distribution","created":"2022-08-23","cited_by_count":4,"area":null},{"id":"2210.14742","title":"Monotonic segmental attention for automatic speech recognition","created":"2022-10-26","cited_by_count":4,"area":null},{"id":"2404.07341","title":"Conformer-1: Robust ASR via Large-Scale Semisupervised Bootstrapping","created":"2024-04-10","cited_by_count":4,"area":null},{"id":"2409.05577","title":"Approximation Bounds for Recurrent Neural Networks with Application to Regression","created":"2024-09-09","cited_by_count":4,"area":null},{"id":"2102.09928","title":"Do End-to-End Speech Recognition Models Care About Context?","created":"2021-02-17","cited_by_count":3,"area":null},{"id":"2107.05382","title":"End-to-End Rich Transcription-Style Automatic Speech Recognition with Semi-Supervised Learning","created":"2021-07-07","cited_by_count":3,"area":null},{"id":"2202.05474","title":"Bench-Marking And Improving Arabic Automatic Image Captioning Through The Use Of Multi-Task Learning Paradigm","created":"2022-02-11","cited_by_count":3,"area":null},{"id":"2202.10594","title":"Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey","created":"2022-02-22","cited_by_count":3,"area":null},{"id":"2204.12308","title":"Supervised Attention in Sequence-to-Sequence Models for Speech Recognition","created":"2022-04-25","cited_by_count":3,"area":null},{"id":"2210.15876","title":"Random Utterance Concatenation Based Data Augmentation for Improving Short-video Speech Recognition","created":"2022-10-28","cited_by_count":3,"area":null},{"id":"2212.04325","title":"Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers","created":"2022-12-07","cited_by_count":3,"area":null},{"id":"2305.17782","title":"RASR2: The RWTH ASR Toolkit for Generic Sequence-to-sequence Speech Recognition","created":"2023-05-28","cited_by_count":3,"area":null},{"id":"2306.11309","title":"Multi-pass Training and Cross-information Fusion for Low-resource End-to-end Accented Speech Recognition","created":"2023-06-20","cited_by_count":3,"area":null},{"id":"2403.08187","title":"Automatic Speech Recognition (ASR) for the Diagnosis of pronunciation of Speech Sound Disorders in Korean children","created":"2024-03-13","cited_by_count":3,"area":null},{"id":"2411.07607","title":"CJST: CTC Compressor based Joint Speech and Text Training for Decoder-Only ASR","created":"2024-11-12","cited_by_count":3,"area":null},{"id":"2101.06511","title":"Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems","created":"2021-01-16","cited_by_count":2,"area":null},{"id":"2103.17142","title":"Compressing 1D Time-Channel Separable Convolutions using Sparse Random Ternary Matrices","created":"2021-03-31","cited_by_count":2,"area":null},{"id":"2106.14459","title":"Recurrent neural network transducer for Japanese and Chinese offline handwritten text recognition","created":"2021-06-28","cited_by_count":2,"area":null},{"id":"2108.10803","title":"Reducing Exposure Bias in Training Recurrent Neural Network Transducers","created":"2021-08-24","cited_by_count":2,"area":null},{"id":"2110.03326","title":"Back from the future: bidirectional CTC decoding using future information in speech recognition","created":"2021-10-07","cited_by_count":2,"area":null},{"id":"2110.08731","title":"Improving End-To-End Modeling for Mispronunciation Detection with Effective Augmentation Mechanisms","created":"2021-10-17","cited_by_count":2,"area":null},{"id":"2111.03952","title":"CALText: Contextual Attention Localization for Offline Handwritten Text","created":"2021-11-06","cited_by_count":2,"area":null},{"id":"2111.08400","title":"Integrated Semantic and Phonetic Post-correction for Chinese Speech Recognition","created":"2021-11-16","cited_by_count":2,"area":null},{"id":"2201.10792","title":"On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR","created":"2022-01-26","cited_by_count":2,"area":null},{"id":"2205.06963","title":"Improved Consistency Training for Semi-Supervised Sequence-to-Sequence ASR via Speech Chain Reconstruction and Self-Transcribing","created":"2022-05-14","cited_by_count":2,"area":null},{"id":"2206.14623","title":"Contextual Density Ratio for Language Model Biasing of Sequence to Sequence ASR Systems","created":"2022-06-29","cited_by_count":2,"area":null},{"id":"2211.11703","title":"Towards continually learning new languages","created":"2022-11-21","cited_by_count":2,"area":null},{"id":"2305.07677","title":"Masked Audio Text Encoders are Effective Multi-Modal Rescorers","created":"2023-05-11","cited_by_count":2,"area":null},{"id":"2305.17356","title":"Bridging the Granularity Gap for Acoustic Modeling","created":"2023-05-27","cited_by_count":2,"area":null}],"next_cursor":"100"}