SOTAVerified

Automatic Speech Recognition

Papers

Showing 18511875 of 3174 papers

TitleStatusHype
DITTO: Data-efficient and Fair Targeted Subset Selection for ASR Accent Adaptation0
Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASR0
Personalized Automatic Speech Recognition Trained on Small Disordered Speech Datasets0
Data Augmentation with Locally-time Reversed Speech for Automatic Speech Recognition0
An Exploration of Self-Supervised Pretrained Representations for End-to-End Speech Recognition0
A Genetic Programming Approach To Zero-Shot Neural Architecture Ranking0
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition0
Input Length Matters: Improving RNN-T and MWER Training for Long-form Telephony Speech Recognition0
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training0
Hierarchical Conditional End-to-End ASR with CTC and Multi-Granular Subword Units0
Knowledge Distillation for Neural Transducers from Large Self-Supervised Pre-trained Models0
Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR0
Improving Confidence Estimation on Out-of-Domain Data for End-to-End Speech Recognition0
FAST-RIR: Fast neural diffuse room impulse response generatorCode1
Enabling On-Device Training of Speech Recognition Models with Federated Dropout0
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.00
Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings0
Internal Language Model Adaptation with Text-Only Data for End-to-End Speech Recognition0
CTC Variations Through New WFST Topologies0
Spell my name: keyword boosted speech recognition0
Is Attention always needed? A Case Study on Language Identification from Speech0
Fast Contextual Adaptation with Neural Associative Memory for On-Device Personalized Speech Recognition0
BERT Attends the Conversation: Improving Low-Resource Conversational ASRCode0
ASR Rescoring and Confidence Estimation with ELECTRA0
Towards efficient end-to-end speech recognition with biologically-inspired neural networks0
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