# Human Vocal Sentiment Analysis

arXiv: https://arxiv.org/abs/1905.08632 · HTML: https://mlsanity.com/paper/1905.08632/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2019.

## Built on by (most cited first, 2 of 2)

- [Sentiment analysis in non-fixed length audios using a Fully Convolutional Neural Network](https://mlsanity.com/paper/2402.02184/) (2024)
- [Iterative Feature Boosting for Explainable Speech Emotion Recognition](https://mlsanity.com/paper/2405.20172/) (2024)

## Abstract (arXiv)

In this paper, we use several techniques with conventional vocal feature extraction (MFCC, STFT), along with deep-learning approaches such as CNN, and also context-level analysis, by providing the textual data, and combining different approaches for improved emotion-level classification. We explore models that have not been tested to gauge the difference in performance and accuracy. We apply hyperparameter sweeps and data augmentation to improve performance. Finally, we see if a real-time approach is feasible, and can be readily integrated into existing systems.