Persian Aut emotional speech database: machine learning-based evaluation and cost-efficient labeling approach

Key Points

• Emotional speech evaluation revealed high accuracy using machine learning techniques in the dataset.
• The evaluation achieved a remarkable accuracy of 85% within the labeling framework for emotional tone.
• Analysis utilized machine learning to efficiently assess emotional speech labeling in the Persian language.
• Supports a cost-efficient labeling approach for improving emotional understanding in speech datasets.