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Robust Speech Recognition
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Speech-enhanced and Noise-aware Networks for Robust Speech Recognition
Investigation of Densely Connected Convolutional Networks with Domain Adversarial Learning for Noise Robust Speech Recognition
A comparison of streaming models and data augmentation methods for robust speech recognition
Sequential Randomized Smoothing for Adversarially Robust Speech Recognition
Wav2vec-Switch: Contrastive Learning from Original-noisy Speech Pairs for Robust Speech Recognition
Interactive Feature Fusion for End-to-End Noise-Robust Speech Recognition
Optimized Power Normalized Cepstral Coefficients towards Robust Deep Speaker Verification
An Investigation of End-to-End Models for Robust Speech Recognition
Domain Adaptation Using Class Similarity for Robust Speech Recognition
Aphasic Speech Recognition using a Mixture of Speech Intelligibility Experts
Deep Learning Based Dereverberation of Temporal Envelopesfor Robust Speech Recognition
Attentive Fusion Enhanced Audio-Visual Encoding for Transformer Based Robust Speech Recognition
Multi-task self-supervised learning for Robust Speech Recognition
Multi-scale Octave Convolutions for Robust Speech Recognition
Does Speech enhancement of publicly available data help build robust Speech Recognition Systems?
Domain Expansion in DNN-based Acoustic Models for Robust Speech Recognition
Speech Recognition with Augmented Synthesized Speech
Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews
Learning Waveform-Based Acoustic Models using Deep Variational Convolutional Neural Networks
On combining features for single-channel robust speech recognition in reverberant environments
Cumulative Adaptation for BLSTM Acoustic Models
Unsupervised Speech Domain Adaptation Based on Disentangled Representation Learning for Robust Speech Recognition
Modality Attention for End-to-End Audio-visual Speech Recognition
Reinforcement Learning Based Speech Enhancement for Robust Speech Recognition
Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition
Learning Noise-Invariant Representations for Robust Speech Recognition
Training Augmentation with Adversarial Examples for Robust Speech Recognition
Scalable Factorized Hierarchical Variational Autoencoder Training
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition
Spectral feature mapping with mimic loss for robust speech recognition
Unsupervised Adaptation with Domain Separation Networks for Robust Speech Recognition
Deep Long Short-Term Memory Adaptive Beamforming Networks For Multichannel Robust Speech Recognition
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition
Robust Speech Recognition Using Generative Adversarial Networks
Unsupervised Domain Adaptation for Robust Speech Recognition via Variational Autoencoder-Based Data Augmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.