Search Results for author:
Found 2 papers, 1 papers with code
Standard Deviation-Based Quantization for Deep Neural Networks
Quantization of deep neural networks is a promising approach that reduces the inference cost, making it feasible to run deep networks on resource-restricted devices.
Using Speech Synthesis to Train End-to-End Spoken Language Understanding Models
End-to-end models are an attractive new approach to spoken language understanding (SLU) in which the meaning of an utterance is inferred directly from the raw audio without employing the standard pipeline composed of a separately trained speech recognizer and natural language understanding module.
Ranked #7 on
Spoken Language Understanding
on Snips-SmartLights
Cannot find the paper you are looking for? You can
Submit a new open access paper.
