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Found 3 papers, 1 papers with code
The RWTH ASR System for TED-LIUM Release 2: Improving Hybrid HMM with SpecAugment
We present a complete training pipeline to build a state-of-the-art hybrid HMM-based ASR system on the 2nd release of the TED-LIUM corpus.
Cumulative Adaptation for BLSTM Acoustic Models
Further, i-vectors were used as an input to the neural network to perform instantaneous speaker and environment adaptation, providing 8\% relative improvement in word error rate on the NIST Hub5 2000 evaluation test set.
RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation
To the best knowledge of the authors, the results obtained when training on the full LibriSpeech training set, are the best published currently, both for the hybrid DNN/HMM and the attention-based systems.
Ranked #24 on
Speech Recognition
on LibriSpeech test-other
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
