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Multi-Channel Automatic Speech Recognition Using Deep Complex Unet

Efficient Large Scale Semi-Supervised Learning For Ctc Based Acoustic Models

Semi-Supervised End-To-End Speech Recognition Via Local Prior Matching

Internal Language Model Estimation For Domain-Adaptive End-To-End Speech Recognition

Streaming Attention-Based Models With Augmented Memory For End-To-End Speech Recognition

Dynamically Weighted Ensemble Models For Automatic Speech Recognition

End-To-End Whispered Speech Recognition With Frequency-Weighted Approaches And Pseudo Whisper Pre-Training

Metric Learning For Keyword Spotting

Dual Application Of Speech Enhancement For Automatic Speech Recognition

Cascade Rnn-Transducer: Syllable Based Streaming On-Device Mandarin Speech Recognition With A Syllable-To-Character Converter

On The Usefulness Of Self-Attention For Automatic Speech Recognition With Transformers

Data Augmentation For End-To-End Code-Switching Speech Recognition