New measurement methods for signal adaptive hearing aids
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1 SIEMENS Josef Chalupper 1 New measurement methods for signal adaptive hearing aids Josef Chalupper Siemens Audiologische Technik, Erlangen
2 SIEMENS Josef Chalupper 2 Motivation modern hearing aids signal processing is signal adaptive! nonlinear and time variant - compression - time constants - adaptive algorithms (classification, noise reduction, adaptive directionality) Behaviour for arbitrary nonstationary signals can not be predicted from stationary. Impact of parameter variations on auditory perception can not be quantified. ==> New analysis methods necessary!
3 SIEMENS Josef Chalupper 3 Requirements for new analysis methods psychoacoustical / audiological relevance ==> properties of human auditory system assessment of all hearing aid features ==> arbitrary (natural) input signals easy-to-understand visualisation ==> use of well-known diagrams ==> PAsHA ( Perceptual Assessment of Hearing Aids )
4 SIEMENS Josef Chalupper 4 PAsHA: Perceptual Assessment of Hearing Aids Aurally adequate analysis of hearing aid input and output signals: critical band level percentile pattern Technical parameters: effective gain, effective compression ratio, effective I/O curve Psychoacoustic parameters: Specific loudness, loudness, sharpness, fluctuation strength, speech intelligibility
5 SIEMENS Josef Chalupper 5 Aurally adequate analyis of hearing aid input and output signals Time signal Critical band filterbank Envelope extraction Percentile analysis FTT 4th order / Gammatone filterbank Auditory temporal window (ERD = 8 ms, f S = 5 Hz) Percentiles in all critical bands Critical band level percentile pattern
6 Critical band level percentile patterns SIEMENS Josef Chalupper 6 Hearing aid input signal Hearing aid output signal f / Hz f / Hz L G / db 6 L G / db z / Bark z / Bark Test signal: speech with door slamming hearing aid : 16-channel-compression, syllabic compression, DSL 1% / 5% / 5% / 95% / 99% percentiles displayed
7 Technical parameters I SIEMENS Josef Chalupper 7 Effective compression ratio: CR eff = 24 1 L I95(z) L I5(z) 24 L (z) L (z) z= 1 O95 O5 Effective I/O-curve: - Form for each percentile x a pair of variates with L Ix und L Ox - Enter this pair of variates into the /L OUT -diagram L OUT / db Einzelwerte statische I/O-Kennlinie effektive I/O-Kennlinie / db
8 Technical parameters II SIEMENS Josef Chalupper 8 Effective gain: - Determine the percentile x of the input signal for a specified level L Ix (e.g. 4 / 58 / 76 db) - Determine the level of the same percentile of the output signal L Ox - Effective gain is: L ox -L Ix 4 Effektive Verstärkung / db = 4 db = 58 db = 76 db f / khz
9 Technical parameters III SIEMENS Josef Chalupper 9 Differential gain: Difference of effective gains: hearing A - hearing aid B 2 15 Effektive Verstärkung 1 B d n / ga i e v e c t i e f = 4 db = 59 db = 78 db f / khz
10 Perceptual relevance SIEMENS Josef Chalupper 1 Subjective data vs. Calculated perceptual distance perceptual distance : euclidian distance of effective gains keine distance < 1 db: no audible differences e d e h i c rs U nte e a r b e r o h gering leicht mittel deutlich Perzeptiver Abstand Increasing perceptual distance results in increasing subjective difference outlook: calculate perceptual distance from specific loudness
11 Psychoacoustic Parameters SIEMENS Josef Chalupper 11 Specific loudness: prerequisite: loudness model for normal and hearing-impaired listeners (e.g. DLM) transform critical band level percentile pattern into specific loudness percentile pattern by applying individual loudness function N (L E ) Loudness: N = sum over all 95%-percentiles of Specific loudness percentile pattern Sharpness: S = weighted sum over all 8%-percentiles of Specific loudness percentile pattern Speech intelligibility: AAI (requires effective compression ratio!) and SII can be calculated from critical band level percentile pattern of speech and noise
12 Example: impact of compression time constants I SIEMENS Josef Chalupper 12 Dual AGC AVC f / Hz f / Hz L G / db 6 L G / db z / Bark z / Bark 5% percentile (average level) similar AVC: high levels exceed UCL!
13 Example: impact of compression time constants II Dual AGC AVC LOUT / db 12 LOUT / db Einzelwerte statische I/O-Kennlinie effektive I/O-Kennlinie LIN / db Einzelwerte statische I/O-Kennlinie effektive I/O-Kennlinie LIN / db Effective I/O-curves: nearly no compression with AVC! SIEMENS Josef Chalupper 13
14 Example: comparison of advanced hearing aids SIEMENS Josef Chalupper 14 Large differences of compression characteristics revealed in 2ccm measurements effective gain / db Effektive Verstärkung = 4 db = 59 db = 78 db f / khz Only a linear offset observed for effective gain (in line with subjective judgements)
15 Summary of PAsHA SIEMENS Josef Chalupper 15 PAsHA: Method for perceptual analysis of nonlinear and adaptive hearing aids takes into account properties of the human hearing system: HTL, UCL, temporal and spectral resolution Calculation of psychoacoustic parameters ==> psychoacustic / audiological relevance Calculation of technical parameters ==> well-known diagrams can be used (easy-to-understand) arbitrary (natural) signals can be used ==> all hearing aid features can be assessd
16 Discussion SIEMENS Josef Chalupper 16 New measurement methods are necessary for modern hearing aids Specification of requirements Selection / development of measurement method(s)! Proposals for requirements and methods are available (Verschuure et al., Leijon, PAsHA...)! Selection and implementation must be supported by hearing aid manufacturers (joint research project?)
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