Papers with Code 아카이브
Unsupervised Speech Recognition
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논문
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Unsupervised Speech Recognition with N-Skipgram and Positional Unigram Matching
A Theory of Unsupervised Speech Recognition
Enhancing Unsupervised Speech Recognition with Diffusion GANs
Supervised Acoustic Embeddings And Their Transferability Across Languages
Simple and Effective Unsupervised Speech Translation
Simple and Effective Unsupervised Speech Synthesis
Towards End-to-end Unsupervised Speech Recognition
Analyzing the Robustness of Unsupervised Speech Recognition
Dynamic Gradient Aggregation for Federated Domain Adaptation
Unsupervised Speech Recognition
Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning
From Semi-supervised to Almost-unsupervised Speech Recognition with Very-low Resource by Jointly Learning Phonetic Structures from Audio and Text Embeddings
Completely Unsupervised Speech Recognition By A Generative Adversarial Network Harmonized With Iteratively Refined Hidden Markov Models
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
Almost-unsupervised Speech Recognition with Close-to-zero Resource Based on Phonetic Structures Learned from Very Small Unpaired Speech and Text Data
A segmental framework for fully-unsupervised large-vocabulary speech recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.