Publication

Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs

2019
Reports

Abstract

Speech-based degree of sleepiness estimation is an emerging research problem. In the literature, this problem has been mainly addressed through modeling of low level of descriptors. This paper investigates an end-to-end approach, where given raw waveform as input, a neural network estimates at its output the degree of sleepiness. Through an investigation on the continuous sleepiness sub-challenge of the INTERSPEECH 2019 Computational Paralinguistics Challenge, we show that the proposed approach consistently yields performance comparable or better than low level descriptor-based, bag-of-audio-words-based and sequence-to-sequence autoencoder feature representation-based regression systems. Furthermore, a confusion matrix analysis on the development set shows that, unlike the best baseline system, the performance of our approach is not centering around a few degrees of sleepiness, but is spread across all the degrees of sleepiness.

Official source

https://infoscience.epfl.ch/entities/publication/c36ff23b-34bb-4864-8dde-22531bc629c4

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2019
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/c36ff23b-34bb-4864-8dde-22531bc629c4

About this result

Related concepts (30)

Deep learning

Deep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.

Artificial neural network

Artificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Speech recognition

Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.

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Estimating The Degree of Sleepiness by Integrating Articulatory Feature Knowledge In Raw Waveform Based CNNs

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