ASR progress report(Wang, Yi-Ling) Server Server IP 1 ssh lenny@140.113.170.49 -p 20203 3 ssh lenny@140.113.170.46 -p 10201 ML-public Click Running SpeechTransformer ICAASP2018 Pending RNN-T Structure Transofrmer RNN-T Reference Code Name Language Developer Speech-Transformer Pytorch - Speech-Transformer Pytorch&Kaldi - Online-Speech-Recognition(RNN-T) Pytorch - PaperWithCode Title Paper Code Source Longformer: The Long-Document Transformer Link Pytorch – - Linformer: Self-Attention with Linear Complexity Link Pytorch1 、 Pytorch2 Facebook Speech-Transformer: A No-Recurrence Sequence-to-Sequence Model for Speech Recognition Link Pytorch1 、 Pytorch2 ICASSP 2018 Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention Link Pytorch1 、 Pytorch2 ICML 2020 Fast Transformers with Clustered Attention Link Pytorch – - Star-Transformer Link Pytorch NAACL 2019 Lite Transformer with Long-Short Range Attention Link Pytorch 、 ICLR 2020 Encoding word order in complex embeddings Link Pytorch ICLR 2020 Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks Link Pytorch ICML 2019 Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing Link 、 中文版 Pytorch Google、CMU Adaptive Attention Span in Transformers Link Pytorch Facebook、ACL 2019 Transformer-XL Link Pytorch ACL 2019 Techinque Name Publisher SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition Interspeech 2019 ? Semantic Mask for Transformer based End-to-End Speech Recognition Microsoft Research ? Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks Google ? State-of-the-art Speech Recognition With Sequence-to-Sequence Models Google ICASSP2019 SYNTHESIZER: Rethinking Self-Attention in Transformer Models ] Google ICLR2021 CP-GAN: CONTEXT PYRAMID GENERATIVE ADVERSARIAL NETWORK FOR SPEECH ENHANCEMENT ] Group meeting ICASSP 2020 Dataset Corpus Language AI Shell Chinese Librispeech English WSJ English Switchboard English Benchmark Result： Corpus Librispeech ICML Learning to Encode Position for Transformer with Continuous Dynamical Model Improving the Gating Mechanism of Recurrent Neural Network EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Stabilizing Transformers for Reinforcement Learning Interspeech Improving Transformer-based End-to-End Speech Recognition with Connectionist Temporal Classification and Language Model Integration Automatic Spelling Correction with Transformer for CTC-based End-to-End Speech Recognition Git Transformer-based online speech recognition system with TensorFlow 2 Reference(Net) Attention_reform1 Attention_reform2 ICLR 2020 Trend of Transformer IBM_transformer Mix https://blog.csdn.net/qq_37236745/article/details/107352273?utm_medium=distribute.pc_relevant.none-task-blog-title-6&spm=1001.2101.3001.4242 Old Releated Paper Name Instution Source Listen, attend and spell: A neural network for large vocabulary conversational speech recognition CMU Google ICASSP2016 A Comparison of Sequence-to-Sequence Models for Speech Recognition Google Interspeech 2017 A comparable study of modeling units for end-to-end Mandarin speech recognition Didi ISCSLP2018* Reference Code Name Language Developer LAS_Mandarin_PyTorch Pytorch LAS End-to-end-ASR-Pytorch Pytorch LAS LAS Structure Structure LAS(Listen, Attend and Spell)
