MFCC and Machine Learning Based Speech Emotion Recognition Over TESS and IEMOCAP Datasets
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Bibliographic record
Abstract
Emotions in speech provide a lot of information about the speaker’s emotional state. This paper presents a classification of emotions using a support vector machine (SVM) with Mel Frequency Cepstrum Coefficient (MFCC) features extracted from the voice signal. We have considered the following five emotions, namely anger, happy, neutral, pleasant surprise and sadness, for classification purposes. The proposed methodology, including SVM-Gaussian and SVM-Quadratic, is tested for its performance on the Toronto Emotion Speech Set (TESS) and Interactive Emotional Dyadic Motion Capture (IEMOCAP) datasets. Our proposed methodology achieved 97% accuracy with TESS and 86% with IEMOCAP datasets, respectively.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it