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Found 5 papers, 0 papers with code
Transformer-based Model for ASR N-Best Rescoring and Rewriting
Voice assistants increasingly use on-device Automatic Speech Recognition (ASR) to ensure speed and privacy.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Personalization of CTC-based End-to-End Speech Recognition Using Pronunciation-Driven Subword Tokenization
Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as contact names remains a challenge.
Acoustic Model Fusion for End-to-end Speech Recognition
Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Learning from Noisy Labels with Noise Modeling Network
Multi-label image classification has generated significant interest in recent years and the performance of such systems often suffers from the not so infrequent occurrence of incorrect or missing labels in the training data.
Towards a New Understanding of the Training of Neural Networks with Mislabeled Training Data
This includes results about the ability of the noisy model to make the same decisions as the clean model and the effects of noise on model performance.
