---
layout: single
title:  "Deep-Neural Baseline"
categories: research 
excerpt: "Introduction a deep baseline for audio classification."
header:
  teaser: assets/figures/3_deep_neural_baselines_teaser.jpg
---

![Self-Replication Robustness](\assets\figures\3_deep_neural_baselines.jpg){:style="display:block; width:30%" .align-right}
The study presents an innovative end-to-end deep learning method to identify sleepiness in spoken language, as part of the Interspeech 2019 ComParE challenge. This method utilizes a deep neural network architecture to analyze audio data directly, eliminating the need for specific feature engineering. This approach not only achieves performance comparable to state-of-the-art models but is also adaptable to various audio classification tasks. For more details, refer to the work by {% cite elsner2019deep %}.