Search Results for author: Wolfgang Roth

Found 13 papers, 3 papers with code

End-to-end Keyword Spotting using Neural Architecture Search and Quantization

no code implementations14 Apr 2021 David Peter, Wolfgang Roth, Franz Pernkopf

This paper introduces neural architecture search (NAS) for the automatic discovery of end-to-end keyword spotting (KWS) models in limited resource environments.

Ranked #15 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 12 metric)

Keyword Spotting Neural Architecture Search +1

Resource-efficient DNNs for Keyword Spotting using Neural Architecture Search and Quantization

2 code implementations18 Dec 2020 David Peter, Wolfgang Roth, Franz Pernkopf

This paper introduces neural architecture search (NAS) for the automatic discovery of small models for keyword spotting (KWS) in limited resource environments.

Keyword Spotting Neural Architecture Search +1

Quantized Neural Networks for Radar Interference Mitigation

no code implementations25 Nov 2020 Johanna Rock, Wolfgang Roth, Paul Meissner, Franz Pernkopf

Radar sensors are crucial for environment perception of driver assistance systems as well as autonomous vehicles.

Autonomous Vehicles Denoising +1

Differentiable TAN Structure Learning for Bayesian Network Classifiers

1 code implementation21 Aug 2020 Wolfgang Roth, Franz Pernkopf

Learning the structure of Bayesian networks is a difficult combinatorial optimization problem.

Combinatorial Optimization

Resource-Efficient Speech Mask Estimation for Multi-Channel Speech Enhancement

no code implementations22 Jul 2020 Lukas Pfeifenberger, Matthias Zöhrer, Günther Schindler, Wolfgang Roth, Holger Fröning, Franz Pernkopf

While machine learning techniques are traditionally resource intensive, we are currently witnessing an increased interest in hardware and energy efficient approaches.

BIG-bench Machine Learning Speech Enhancement

Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning (Full Version)

no code implementations10 Jul 2019 Bernhard K. Aichernig, Roderick Bloem, Masoud Ebrahimi, Martin Horn, Franz Pernkopf, Wolfgang Roth, Astrid Rupp, Martin Tappler, Markus Tranninger

Therefore, there is considerable interest in learning such hybrid behavior by means of machine learning which requires sufficient and representative training data covering the behavior of the physical system adequately.

BIG-bench Machine Learning

Parameterized Structured Pruning for Deep Neural Networks

no code implementations12 Jun 2019 Guenther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Froening

As a result, PSP maintains prediction performance, creates a substantial amount of sparsity that is structured and, thus, easy and efficient to map to a variety of massively parallel processors, which are mandatory for utmost compute power and energy efficiency.

Quantization

N-Ary Quantization for CNN Model Compression and Inference Acceleration

no code implementations ICLR 2019 Günther Schindler, Wolfgang Roth, Franz Pernkopf, Holger Fröning

In this work we propose a method for weight and activation quantization that is scalable in terms of quantization levels (n-ary representations) and easy to compute while maintaining the performance close to full-precision CNNs.

Clustering Model Compression +1

Discrete-Valued Neural Networks Using Variational Inference

no code implementations ICLR 2018 Wolfgang Roth, Franz Pernkopf

The increasing demand for neural networks (NNs) being employed on embedded devices has led to plenty of research investigating methods for training low precision NNs.

Quantization Variational Inference

Cannot find the paper you are looking for? You can Submit a new open access paper.