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Noisy Speech Recognition

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논문

이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.

Efficient Extraction of Noise-Robust Discrete Units from Self-Supervised Speech Models

Direction-Aware Joint Adaptation of Neural Speech Enhancement and Recognition in Real Multiparty Conversational Environments

Visual Context-driven Audio Feature Enhancement for Robust End-to-End Audio-Visual Speech Recognition

Improving Noise Robustness of Contrastive Speech Representation Learning with Speech Reconstruction

Speech Recognition With No Speech Or With Noisy Speech Beyond English

An Investigation of End-to-End Multichannel Speech Recognition for Reverberant and Mismatch Conditions

A Convolutional Neural Network model based on Neutrosophy for Noisy Speech Recognition

The PyTorch-Kaldi Speech Recognition Toolkit

Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline

An online sequence-to-sequence model for noisy speech recognition

A comprehensive study of batch construction strategies for recurrent neural networks in MXNet

Invariant Representations for Noisy Speech Recognition

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

Deep Speech: Scaling up end-to-end speech recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.