1 Improved Subjective Weighting Function ANSI C63.19 Working Group Submitted by Stephen Julstrom for October 2, 2007.

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1 Improved Subjective Weighting Function ANSI C63.19 Working Group Submitted by Stephen Julstrom for October 2, 2007

2 In the context of C63.19, the subjective noise-weighting function should predict the degree to which any undesired audio frequency pickup interferes with the desired use of the hearing aid. Study results indicate that the degree of subjective interference is largely a matter of annoyance and not of intelligibility (i.e., noise can be annoying even though the speech is still intelligible). Analysis of the results from the telecoil mode interference study indicates that user annoyance and resultant acceptability correlate strongly with simple audibility of the interference (in the presence of speech). From the results of the testing employing eight differing noise types, it can be said that A-weighting is a reasonable, but not ideal predictor, in the present context. In the following cumulative distribution graphs from the study report, the ideal weighting function would have given identical S/N results for all eight noise types (allowing for random experimental variation), with no consistent bias related to noise type. The Goal of Subjective Weighting

3 (In viewing the graphs, the 80-90% range in the distribution is the most significant for comparison, since it includes the most subjects while excluding the outliers in the top few percent.) Telecoil Mode Test Results Using A-Weighting

4 There is a roughly 10 dB spread of S/N judgments among the noise types. In comparison to GSM, UMTS and FHSS appear to require higher S/N, while TDMA and Display noise appear to require lower S/N. This is because, on a relative basis, A-weighting under-predicts the audibility of the former noise types and over-predicts the audibility of the latter. An improved weighting function should increase somewhat the emphasis on the lower frequency content and the more impulsive nature of UMTS and FHSS, while de-emphasizing the high frequency noise character of TDMA and Display noise. (Interestingly iDEN has some of both sets of characteristics, leaving it coincidentally well-represented by A-weighting.) In addition to the need to respond to the impulsive nature of some signals, a desire to measure the level of the interference while it is “on” (the WD transmission is often intermittent) further suggests the use of quasi-peak detection (roughly as employed by CISPR and ITU-R 468). The extreme 6 kHz region emphasis introduced by ITU-R 468 does not appear to be called for in this application. Indicators for a New Weighting Function

Hz 12.2 kHz Hz Hz 369 Hz 3 kHz, 2 nd order D.F. = x x A-weighted X2X2 X Hz 4 msec TC 550 msec TC Peak DetectorRMS Level Measurement (equivalent to 2 msec TC w/linear level measurement) Similar to CISPR Quasi-Peak Detection 2.6 Hz, 2 nd order D.F. = 0.81 Slow, averaging response such as VU meter dynamics for steady state reading in A-Weighting  Alternate Weighting

6 Slightly enhanced lower frequency sensitivity: Justifiable on the basis that the interference will typically be heard at a 40 to 50 phon level, rather than the 30 phon level that was the original basis for A-weighting. Significantly reduced high frequency sensitivity: Justifiable in light of the probable uncorrected or uncorrectable high frequency hearing loss of the test subjects at the typical noise levels in the presence of typically 65 dB-SPL equivalent speech. Quasi-Peak Detection: Justifiable in light of the ear’s probable sensitivity to impulsive sounds with low average energy and also in light of the inclusion of similar detection in the related CISPR and ITU-R 468 standards. While the quasi- peak detection defined here is not dissimilar from those of the other standards, it is more simply and clearly mathematically defined and works well for the test signals evaluated. Plausible Justifications for the Specific Changes

7 The previous ~10 dB spread in the 80-90% areas is reduced to ~4 dB, with much of that being random variation, rather than consistent bias related to noise type. Telecoil Mode Test Results Using Alternate Weighting

8 Applicability to RF Interference The envelope of the RF amplitude modulation is the common origin for both RF interference and baseband audio frequency magnetic interference (except for display noise), resulting in a very similar audible character to both interferences: The square law detection of RF interference vs. the linear pickup of baseband magnetic interference likely does not result in spectra of such a different nature that they would significantly contradict either the study results or the alternate weighting derived from them. In the case of pure pulse waveforms such as GSM, FHSS, and DSSS, the recovered spectrum is not changed at all by the square law detection. The direct magnetic interference pickup effectively applies a “telecoil response” to the RF modulation spectrum; that is, a 1 st order rolloff below 1 kHz. Thus, RF interference will have relatively somewhat more lower frequency content, in comparison to the corresponding signals as heard by the subjects in the telecoil mode study. The difference is fairly small, though, within the limited lower frequency range of potential audible interest, and should be adequately accounted for by the frequency weighting. Again, the difference is not so great as to likely contradict the study results or the derived weighting. Although derived from telecoil mode study results, the new modified weighting function should likely have equal applicability to RF interference, allowing a common weighting method to be used for both measurements.

9 Addendum: Specific Changes in Measured Levels The table below shows the shift in dB resulting from measurement of the various noise types using the new weighting in comparison to A-weighted measurements. As can be seen, the 1 kHz sine wave reference sensitivity does not shift. The results were modeled using the continuous noise recordings of the telecoil mode study. The “T-coil response” column numbers were subtracted from the corresponding curves in the original study data of slide 3 to obtain the graphs of slide 7, giving the test results as they would have occurred had the noise samples been normalized to the same level using the new weighting (plus the telecoil response) instead of A-weighting. The dB shifts of the “RFI response” column can similarly be applied to RFI study results using related source material to predict their results had the new weighting been used instead of A-weighting.