{"total":65,"rows":[{"id":"2111.01690","title":"Recent Advances in End-to-End Automatic Speech Recognition","created":"2021-11-02","cited_by_count":140,"area":null},{"id":"2304.06795","title":"Efficient Sequence Transduction by Jointly Predicting Tokens and Durations","created":"2023-04-13","cited_by_count":58,"area":null},{"id":"2206.13236","title":"Pruned RNN-T for fast, memory-efficient ASR training","created":"2022-06-23","cited_by_count":46,"area":null},{"id":"2103.09935","title":"Advancing RNN Transducer Technology for Speech Recognition","created":"2021-03-17","cited_by_count":44,"area":null},{"id":"2109.07513","title":"Tied & Reduced RNN-T Decoder","created":"2021-09-15","cited_by_count":36,"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":"2110.01500","title":"Factorized Neural Transducer for Efficient Language Model Adaptation","created":"2021-09-27","cited_by_count":32,"area":null},{"id":"2102.07739","title":"Personalization Strategies for End-to-End Speech Recognition Systems","created":"2021-02-15","cited_by_count":26,"area":null},{"id":"2103.08393","title":"Wav2vec-C: A Self-supervised Model for Speech Representation Learning","created":"2021-03-09","cited_by_count":25,"area":null},{"id":"2203.15952","title":"4-bit Conformer with Native Quantization Aware Training for Speech Recognition","created":"2022-03-29","cited_by_count":24,"area":null},{"id":"2210.07353","title":"JOIST: A Joint Speech and Text Streaming Model For ASR","created":"2022-10-13","cited_by_count":24,"area":null},{"id":"2109.14320","title":"Google Neural Network Models for Edge Devices: Analyzing and Mitigating Machine Learning Inference Bottlenecks","created":"2021-09-29","cited_by_count":23,"area":null},{"id":"2202.13155","title":"Integrating Text Inputs For Training and Adapting RNN Transducer ASR Models","created":"2022-02-26","cited_by_count":20,"area":null},{"id":"2203.00006","title":"Towards Reducing the Need for Speech Training Data To Build Spoken Language Understanding Systems","created":"2022-02-26","cited_by_count":20,"area":null},{"id":"2104.02207","title":"Dissecting User-Perceived Latency of On-Device E2E Speech Recognition","created":"2021-04-06","cited_by_count":19,"area":null},{"id":"2105.00858","title":"On Addressing Practical Challenges for RNN-Transducer","created":"2021-04-27","cited_by_count":19,"area":null},{"id":"2106.02302","title":"Minimum Word Error Rate Training with Language Model Fusion for End-to-End Speech Recognition","created":"2021-06-04","cited_by_count":19,"area":null},{"id":"2203.00888","title":"Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems","created":"2022-03-02","cited_by_count":17,"area":null},{"id":"2208.13321","title":"Turn-Taking Prediction for Natural Conversational Speech","created":"2022-08-29","cited_by_count":15,"area":null},{"id":"2404.09841","title":"Anatomy of Industrial Scale Multilingual ASR","created":"2024-04-15","cited_by_count":14,"area":null},{"id":"2104.02882","title":"FSR: Accelerating the Inference Process of Transducer-Based Models by Applying Fast-Skip Regularization","created":"2021-04-07","cited_by_count":11,"area":null},{"id":"2108.07493","title":"A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems","created":"2021-08-17","cited_by_count":11,"area":null},{"id":"2201.10240","title":"Improving the fusion of acoustic and text representations in RNN-T","created":"2022-01-25","cited_by_count":11,"area":null},{"id":"2204.06164","title":"A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes","created":"2022-04-13","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":"2211.03541","title":"Multi-blank Transducers for Speech Recognition","created":"2022-11-04","cited_by_count":11,"area":null},{"id":"2212.01992","title":"Fast and accurate factorized neural transducer for text adaption of end-to-end speech recognition models","created":"2022-12-05","cited_by_count":11,"area":null},{"id":"2110.03841","title":"Input Length Matters: Improving RNN-T and MWER Training for Long-form Telephony Speech Recognition","created":"2021-10-08","cited_by_count":10,"area":null},{"id":"2302.08917","title":"Massively Multilingual Shallow Fusion with Large Language Models","created":"2023-02-17","cited_by_count":10,"area":null},{"id":"2104.02176","title":"Dynamic Encoder Transducer: A Flexible Solution For Trading Off Accuracy For Latency","created":"2021-04-05","cited_by_count":9,"area":null},{"id":"2108.08405","title":"Integrating Dialog History into End-to-End Spoken Language Understanding Systems","created":"2021-08-18","cited_by_count":9,"area":null},{"id":"2207.06872","title":"Data Augmentation for Low-Resource Quechua ASR Improvement","created":"2022-07-14","cited_by_count":9,"area":null},{"id":"2208.13916","title":"A Language Agnostic Multilingual Streaming On-Device ASR System","created":"2022-08-29","cited_by_count":9,"area":null},{"id":"2102.11531","title":"Memory-efficient Speech Recognition on Smart Devices","created":"2021-02-23","cited_by_count":8,"area":null},{"id":"2105.07071","title":"Listen with Intent: Improving Speech Recognition with Audio-to-Intent Front-End","created":"2021-05-14","cited_by_count":8,"area":null},{"id":"2108.12074","title":"4-bit Quantization of LSTM-based Speech Recognition Models","created":"2021-08-27","cited_by_count":8,"area":null},{"id":"2103.00768","title":"Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models","created":"2021-03-01","cited_by_count":7,"area":null},{"id":"2104.03842","title":"RNN Transducer Models For Spoken Language Understanding","created":"2021-04-08","cited_by_count":7,"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":"2307.14132","title":"CIF-T: A Novel CIF-based Transducer Architecture for Automatic Speech Recognition","created":"2023-07-26","cited_by_count":6,"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":"2111.01272","title":"Sequence Transduction with Graph-based Supervision","created":"2021-11-01","cited_by_count":4,"area":null},{"id":"2303.00786","title":"Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training","created":"2023-03-01","cited_by_count":4,"area":null},{"id":"2104.14346","title":"Bridging the gap between streaming and non-streaming ASR systems bydistilling ensembles of CTC and RNN-T models","created":"2021-04-25","cited_by_count":3,"area":null},{"id":"2203.16868","title":"Memory-Efficient Training of RNN-Transducer with Sampled Softmax","created":"2022-03-31","cited_by_count":3,"area":null},{"id":"2208.13322","title":"Streaming Intended Query Detection using E2E Modeling for Continued Conversation","created":"2022-08-29","cited_by_count":3,"area":null},{"id":"2304.00173","title":"Lego-Features: Exporting modular encoder features for streaming and deliberation ASR","created":"2023-03-31","cited_by_count":3,"area":null},{"id":"2106.04275","title":"Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition","created":"2021-06-08","cited_by_count":2,"area":null},{"id":"2203.15176","title":"Improving Generalization of Deep Neural Network Acoustic Models with Length Perturbation and N-best Based Label Smoothing","created":"2022-03-29","cited_by_count":2,"area":null},{"id":"2307.12134","title":"Modality Confidence Aware Training for Robust End-to-End Spoken Language Understanding","created":"2023-07-22","cited_by_count":2,"area":null},{"id":"2205.14664","title":"Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases","created":"2022-05-29","cited_by_count":1,"area":null},{"id":"2207.14736","title":"Multiple-hypothesis RNN-T Loss for Unsupervised Fine-tuning and Self-training of Neural Transducer","created":"2022-07-29","cited_by_count":1,"area":null},{"id":"2210.16238","title":"Contextual-Utterance Training for Automatic Speech Recognition","created":"2022-10-27","cited_by_count":1,"area":null},{"id":"2211.16270","title":"Neural Transducer Training: Reduced Memory Consumption with Sample-wise Computation","created":"2022-11-29","cited_by_count":1,"area":null},{"id":"2304.00171","title":"Practical Conformer: Optimizing size, speed and flops of Conformer for on-Device and cloud ASR","created":"2023-03-31","cited_by_count":1,"area":null},{"id":"2308.10107","title":"Bayes Risk Transducer: Transducer with Controllable Alignment Prediction","created":"2023-08-19","cited_by_count":1,"area":null},{"id":"2401.11645","title":"Streaming Bilingual End-to-End ASR model using Attention over Multiple Softmax","created":"2024-01-22","cited_by_count":1,"area":null},{"id":"2105.06253","title":"Exploring CTC Based End-to-End Techniques for Myanmar Speech Recognition","created":"2021-05-13","cited_by_count":0,"area":null},{"id":"2201.12105","title":"Improving End-to-End Models for Set Prediction in Spoken Language Understanding","created":"2022-01-28","cited_by_count":0,"area":null},{"id":"2303.12300","title":"Exploring Turkish Speech Recognition via Hybrid CTC/Attention Architecture and Multi-feature Fusion Network","created":"2023-03-22","cited_by_count":0,"area":null},{"id":"2305.10680","title":"Accurate and Reliable Confidence Estimation Based on Non-Autoregressive End-to-End Speech Recognition System","created":"2023-05-18","cited_by_count":0,"area":null},{"id":"2305.15536","title":"RAND: Robustness Aware Norm Decay For Quantized Seq2seq Models","created":"2023-05-24","cited_by_count":0,"area":null},{"id":"2305.18596","title":"Building Accurate Low Latency ASR for Streaming Voice Search","created":"2023-05-29","cited_by_count":0,"area":null},{"id":"2306.06954","title":"Multi-View Frequency-Attention Alternative to CNN Frontends for Automatic Speech Recognition","created":"2023-06-12","cited_by_count":0,"area":null},{"id":"2312.09463","title":"Partial Rewriting for Multi-Stage ASR","created":"2023-12-08","cited_by_count":0,"area":null}],"next_cursor":null}