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20162020
most citedA low latency ASR-free end to end spoken language understanding system

2 citations · 2 across the 1 of their papers we have counts for

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eess.AS2019

Speech Model Pre-training for End-to-End Spoken Language Understanding

Loren Lugosch, Mirco Ravanelli, Patrick Ignoto +2

Whereas conventional spoken language understanding (SLU) systems map speech to text, and then text to intent, end-to-end SLU systems map speech directly to intent through a single…

eess.AS2018

Efficient keyword spotting using time delay neural networks

Samuel Myer, Vikrant Singh Tomar

This paper describes a novel method of live keyword spotting using a two-stage time delay neural network. The model is trained using transfer learning: initial training with phone…

eess.AS2018

Tone Recognition Using Lifters and CTC

Loren Lugosch, Vikrant Singh Tomar

In this paper, we present a new method for recognizing tones in continuous speech for tonal languages. The method works by converting the speech signal to a cepstrogram, extracting…