On the importance of phase in human speech recognition
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we analyze the effects of uncertainty in the phase of speech signals on the word recognition error rate of human listeners. The motivating goal is to get a quantitative measure on the importance of phase in automatic speech recognition by studying the effects of phase uncertainty on human perception. Listening tests were conducted for 18 listeners under different phase uncertainty and signal-to-noise ratio (SNR) conditions. These results indicate that a small amount of phase error or uncertainty does not affect the recognition rate, but a large amount of phase uncertainty significantly affects the recognition rate. The degree of the importance of phase also seems to be an SNR-dependent one, such that at lower SNRs the effects of phase uncertainty are more pronounced than at higher SNRs. For example, at an SNR of -10 dB, having random phases at all frequencies results in a word error rate (WER) of 63% compared to 24% if the phase was unaltered. In comparison, at 0 dB, random phase results in a 25% WER as compared to 11% for the unaltered phase case. Listening tests were also conducted for the case of reconstructed phase based on the least square error estimation approach. The results indicate that the recognition rate for the reconstructed phase case is very close to that of the perfect phase case (a WER difference of 4% on average).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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