most citedDynamic curriculum learning via data parameters for noise robust keyword spotting

2 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

eess.AS20212 cited

Dynamic curriculum learning via data parameters for noise robust keyword spotting

Takuya Higuchi, Shreyas Saxena, Mehrez Souden +3

We propose dynamic curriculum learning via data parameters for noise robust keyword spotting. Data parameter learning has recently been introduced for image processing, where weigh…

cs.SD2020

Optimize what matters: Training DNN-HMM Keyword Spotting Model Using End Metric

Ashish Shrivastava, Arnav Kundu, Chandra Dhir +2

Deep Neural Network--Hidden Markov Model (DNN-HMM) based methods have been successfully used for many always-on keyword spotting algorithms that detect a wake word to trigger a dev…

eess.AS20201 cited

Stacked 1D convolutional networks for end-to-end small footprint voice trigger detection

Takuya Higuchi, Mohammad Ghasemzadeh, Kisun You +1

We propose a stacked 1D convolutional neural network (S1DCNN) for end-to-end small footprint voice trigger detection in a streaming scenario. Voice trigger detection is an importan…

eess.AS2020

Hybrid Transformer/CTC Networks for Hardware Efficient Voice Triggering

Saurabh Adya, Vineet Garg, Siddharth Sigtia +2

We consider the design of two-pass voice trigger detection systems. We focus on the networks in the second pass that are used to re-score candidate segments obtained from the first…

eess.AS2020

Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech Synthesis

Ting-Yao Hu, Ashish Shrivastava, Oncel Tuzel +1

We present a method to generate speech from input text and a style vector that is extracted from a reference speech signal in an unsupervised manner, i.e., no style annotation, suc…