Talker- and language-specific effects on speech intelligibility in noise assessed with bilingual talkers: Which language is more robust against noise and reverberation?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Investigate talker- and language-specific aspects of speech intelligibility in noise and reverberation using highly comparable matrix sentence tests across languages. DESIGN: Matrix sentences spoken by German/Russian and German/Spanish bilingual talkers were recorded. These sentences were used to measure speech reception thresholds (SRTs) with native listeners in the respective languages in different listening conditions (stationary and fluctuating noise, multi-talker babble, reverberated speech-in-noise condition). STUDY SAMPLE: Four German/Russian and four German/Spanish bilingual talkers; 20 native German-speaking, 10 native Russian-speaking, and 10 native Spanish-speaking listeners. RESULTS: Across-talker SRT differences of up to 6 dB were found for both groups of bilinguals. SRTs of German/Russian bilingual talkers were the same in both languages. SRTs of German/Spanish bilingual talkers were higher when they talked in Spanish than when they talked in German. The benefit from listening in the gaps was similar across all languages. The detrimental effect of reverberation was larger for Spanish than for German and Russian. CONCLUSIONS: Within the limitations set by the number and slight accentedness of talkers and other possible confounding factors, talker- and test-condition-dependent differences were isolated from the language effect: Russian and German exhibited similar intelligibility in noise and reverberation, whereas Spanish was more impaired in these situations.
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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 | 0.002 |
| 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