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Automatic Speech Recognition

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Showing 1651–1700 of 3174 papers

TitleStatusHype
Multiple-hypothesis RNN-T Loss for Unsupervised Fine-tuning and Self-training of Neural Transducer—0
Multiple Representation Transfer from Large Language Models to End-to-End ASR Systems—0
Multiple topic identification in human/human conversations—0
MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech—0
Multiresolution and Multimodal Speech Recognition with Transformers—0
Multi-resolution location-based training for multi-channel continuous speech separation—0
Alternate Intermediate Conditioning with Syllable-level and Character-level Targets for Japanese ASR—0
Multi-Span Acoustic Modelling using Raw Waveform Signals—0
Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications - A Case Study on German Oral History Interviews—0
Multistage Fine-tuning Strategies for Automatic Speech Recognition in Low-resource Languages—0
Multi-Stage Multi-Modal Pre-Training for Automatic Speech Recognition—0
Multi-stage Progressive Compression of Conformer Transducer for On-device Speech Recognition—0
Multi-Stream End-to-End Speech Recognition—0
Multi-style Training for South African Call Centre Audio—0
Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR—0
Multi-Talker MVDR Beamforming Based on Extended Complex Gaussian Mixture Model—0
Multitask-Based Joint Learning Approach To Robust ASR For Radio Communication Speech—0
Multi-task Language Modeling for Improving Speech Recognition of Rare Words—0
Multitask Learning for Adaptive Quality Estimation of Automatically Transcribed Utterances—0
Multi-Task Learning for End-to-End ASR Word and Utterance Confidence with Deletion Prediction—0
Multitask Learning for Low Resource Spoken Language Understanding—0
Multi-task Learning Of Deep Neural Networks For Audio Visual Automatic Speech Recognition—0
Multi-task Learning of Spoken Language Understanding by Integrating N-Best Hypotheses with Hierarchical Attention—0
Multi-task Learning with Cross Attention for Keyword Spotting—0
Multi-task RNN-T with Semantic Decoder for Streamable Spoken Language Understanding—0
Multi-Task Self-Supervised Pre-Training for Music Classification—0
Multi-Temporal Lip-Audio Memory for Visual Speech Recognition—0
Multi-turn RNN-T for streaming recognition of multi-party speech—0
Multi-user VoiceFilter-Lite via Attentive Speaker Embedding—0
Multi-view Attention-based Speech Enhancement Model for Noise-robust Automatic Speech Recognition—0
Multi-View Frequency-Attention Alternative to CNN Frontends for Automatic Speech Recognition—0
Multi-view Frequency LSTM: An Efficient Frontend for Automatic Speech Recognition—0
MuST-C: a Multilingual Speech Translation Corpus—0
Mutually-Constrained Monotonic Multihead Attention for Online ASR—0
My Science Tutor (MyST) -- A Large Corpus of Children's Conversational Speech—0
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition—0
Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances—0
N-best T5: Robust ASR Error Correction using Multiple Input Hypotheses and Constrained Decoding Space—0
NeMo: a toolkit for building AI applications using Neural Modules—0
NEST-RQ: Next Token Prediction for Speech Self-Supervised Pre-Training—0
Neural approaches to spoken content embedding—0
Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks—0
Neural Kalman Filtering for Speech Enhancement—0
Neural Language Model Pruning for Automatic Speech Recognition—0
Neural Machine Translation for Multilingual Grapheme-to-Phoneme Conversion—0
Neural model robustness for skill routing in large-scale conversational AI systems: A design choice exploration—0
Neural Network-Based Modeling of Phonetic Durations—0
Neural Network Language Modeling with Letter-based Features and Importance Sampling—0
Neural Speech Translation at AppTek—0
Neural Transducer Training: Reduced Memory Consumption with Sample-wise Computation—0
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