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Automatic Speech Recognition

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Showing 801–825 of 3174 papers

TitleStatusHype
ML-SUPERB 2.0: Benchmarking Multilingual Speech Models Across Modeling Constraints, Languages, and Datasets—0
Towards Unsupervised Speech Recognition Without Pronunciation ModelsCode0
Transformer-based Model for ASR N-Best Rescoring and Rewriting—0
Tag and correct: high precision post-editing approach to correction of speech recognition errors—0
Reading Miscue Detection in Primary School through Automatic Speech Recognition—0
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection—0
Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter—0
ASTRA: Aligning Speech and Text Representations for Asr without Sampling—0
MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations—0
Pitch-Aware RNN-T for Mandarin Chinese Mispronunciation Detection and Diagnosis—0
LoRA-Whisper: Parameter-Efficient and Extensible Multilingual ASR—0
Improving Zero-Shot Chinese-English Code-Switching ASR with kNN-CTC and Gated Monolingual Datastores—0
To Distill or Not to Distill? On the Robustness of Robust Knowledge DistillationCode0
Flexible Multichannel Speech Enhancement for Noise-Robust Frontend—0
Hypernetworks for Personalizing ASR to Atypical Speech—0
Joint Beam Search Integrating CTC, Attention, and Transducer Decoders—0
Text Injection for Neural Contextual Biasing—0
Enhancing CTC-based speech recognition with diverse modeling units—0
Task Arithmetic can Mitigate Synthetic-to-Real Gap in Automatic Speech Recognition—0
Error-preserving Automatic Speech Recognition of Young English Learners' LanguageCode0
Efficiently Train ASR Models that Memorize Less and Perform Better with Per-core Clipping—0
Keyword-Guided Adaptation of Automatic Speech Recognition—0
Whistle: Data-Efficient Multilingual and Crosslingual Speech Recognition via Weakly Phonetic Supervision—0
Enabling ASR for Low-Resource Languages: A Comprehensive Dataset Creation Approach—0
Wav2Prompt: End-to-End Speech Prompt Generation and Tuning For LLM in Zero and Few-shot Learning—0
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