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Automatic Speech Recognition

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Showing 2151–2200 of 3174 papers

TitleStatusHype
LV-CTC: Non-autoregressive ASR with CTC and latent variable models—0
Lyrics-to-Audio Alignment by Unsupervised Discovery of Repetitive Patterns in Vowel Acoustics—0
Machine Speech Chain with One-shot Speaker Adaptation—0
MADI: Inter-domain Matching and Intra-domain Discrimination for Cross-domain Speech Recognition—0
Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0—0
Mai Ho'omāuna i ka 'Ai: Language Models Improve Automatic Speech Recognition in Hawaiian—0
Make More of Your Data: Minimal Effort Data Augmentation for Automatic Speech Recognition and Translation—0
Malayalam Speech Corpus: Design and Development for Dravidian Language—0
MAM: Masked Acoustic Modeling for End-to-End Speech-to-Text Translation—0
Mandarin-English Code-Switching Speech Recognition System for Specific Domain—0
ManWav: The First Manchu ASR Model—0
Masked Audio Text Encoders are Effective Multi-Modal Rescorers—0
Mask scalar prediction for improving robust automatic speech recognition—0
MASRI-HEADSET: A Maltese Corpus for Speech Recognition—0
Massive End-to-end Models for Short Search Queries—0
Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters—0
Massively Multilingual Shallow Fusion with Large Language Models—0
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning—0
MathBridge: A Large Corpus Dataset for Translating Spoken Mathematical Expressions into LaTeX Formulas for Improved Readability—0
Maximum a Posteriori Adaptation of Network Parameters in Deep Models—0
M-BEST-RQ: A Multi-Channel Speech Foundation Model for Smart Glasses—0
Measuring the Impact of Individual Domain Factors in Self-Supervised Pre-Training—0
MEDSAGE: Enhancing Robustness of Medical Dialogue Summarization to ASR Errors with LLM-generated Synthetic Dialogues—0
MeetDot: Videoconferencing with Live Translation Captions—0
Mel Frequency Spectral Domain Defenses against Adversarial Attacks on Speech Recognition Systems—0
Mel-FullSubNet: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR—0
Memory Augmented Lookup Dictionary based Language Modeling for Automatic Speech Recognition—0
Memory-Efficient Training of RNN-Transducer with Sampled Softmax—0
Memory Visualization for Gated Recurrent Neural Networks in Speech Recognition—0
Mesures linguistiques automatiques pour l’évaluation des systèmes de Reconnaissance Automatique de la Parole (Automated linguistic measures for automatic speech recognition systems’ evaluation)—0
Meta Auxiliary Learning for Low-resource Spoken Language Understanding—0
META-CAT: Speaker-Informed Speech Embeddings via Meta Information Concatenation for Multi-talker ASR—0
Meta Learning for End-to-End Low-Resource Speech Recognition—0
Meta-Learning for improving rare word recognition in end-to-end ASR—0
SMILE: Speech Meta In-Context Learning for Low-Resource Language Automatic Speech Recognition—0
MF-AED-AEC: Speech Emotion Recognition by Leveraging Multimodal Fusion, Asr Error Detection, and Asr Error Correction—0
Microphone Array Geometry Independent Multi-Talker Distant ASR: NTT System for the DASR Task of the CHiME-8 Challenge—0
MIMO Self-attentive RNN Beamformer for Multi-speaker Speech Separation—0
Minimally Supervised Written-to-Spoken Text Normalization—0
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition—0
Mitigating Noisy Inputs for Question Answering—0
MIXPGD: Hybrid Adversarial Training for Speech Recognition Systems—0
MixSpeech: Data Augmentation for Low-resource Automatic Speech Recognition—0
Mixture Encoder for Joint Speech Separation and Recognition—0
Combining TF-GridNet and Mixture Encoder for Continuous Speech Separation for Meeting Transcription—0
Mixture-of-Expert Conformer for Streaming Multilingual ASR—0
Mixture of LoRA Experts for Low-Resourced Multi-Accent Automatic Speech Recognition—0
Mixtures of Deep Neural Experts for Automated Speech Scoring—0
MLCA-AVSR: Multi-Layer Cross Attention Fusion based Audio-Visual Speech Recognition—0
ML-LMCL: Mutual Learning and Large-Margin Contrastive Learning for Improving ASR Robustness in Spoken Language Understanding—0
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