Multimodal and Spectral Degradation Effects on Speech and Emotion Recognition in Adult Listeners
Bibliographic record
Abstract
For cochlear implant (CI) users, degraded spectral input hampers the understanding of prosodic vocal emotion, especially in difficult listening conditions. Using a vocoder simulation of CI hearing, we examined the extent to which informative multimodal cues in a talker's spoken expressions improve normal hearing (NH) adults' speech and emotion perception under different levels of spectral degradation (two, three, four, and eight spectral bands). Participants repeated the words verbatim and identified emotions (among four alternative options: happy, sad, angry, and neutral) in meaningful sentences that are semantically congruent with the expression of the intended emotion. Sentences were presented in their natural speech form and in speech sampled through a noise-band vocoder in sound (auditory-only) and video (auditory-visual) recordings of a female talker. Visual information had a more pronounced benefit in enhancing speech recognition in the lower spectral band conditions. Spectral degradation, however, did not interfere with emotion recognition performance when dynamic visual cues in a talker's expression are provided as participants scored at ceiling levels across all spectral band conditions. Our use of familiar sentences that contained congruent semantic and prosodic information have high ecological validity, which likely optimized listener performance under simulated CI hearing and may better predict CI users' outcomes in everyday listening contexts.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".