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Found 3 papers, 1 papers with code
Visual Features for Context-Aware Speech Recognition
We are working on a corpus of "how-to" videos from the web, and the idea is that an object that can be seen ("car"), or a scene that is being detected ("kitchen") can be used to condition both models on the "context" of the recording, thereby reducing perplexity and improving transcription.
EESEN: End-to-End Speech Recognition using Deep RNN Models and WFST-based Decoding
The performance of automatic speech recognition (ASR) has improved tremendously due to the application of deep neural networks (DNNs).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Kaldi+PDNN: Building DNN-based ASR Systems with Kaldi and PDNN
Using these recipes, we can build up multiple systems including DNN hybrid systems, convolutional neural network (CNN) systems and bottleneck feature systems.
