Ripple density resolution for various rippled-noise patterns

Abstract

Ripple-density resolution was measured in normal humans using rippled noise with a phase-reversal test. The principle of the test was to find the highest ripple density at which an interchange of spectral peak and trough positions (the phase reversal) is detectable. Different rippled noise patterns were used: (i) either frequency-proportional or constant ripple spacing; (ii) various bandwidth; and (iii) either steep or shallow slopes of the spectrum envelope. When tested with frequency-proportional rippled noise, ripple-density resolution as expressed in relative units (the center frequency to ripple spacing ratio) little depended on frequency within a range of 1 to 8 kHz: from 11.4 at 1 kHz to 14.9 at 8 kHz, mean 13.1. These values were virtually independent on noise bandwidth. When tested with constant ripple spacing, the resolution was of similar values taking the relative ripple density at the lower part of the passband. Being measured by noise with steep spectral edges, the resolution was five units higher than it was for shallow-enveloped spectra, thus suggesting some edge effects at the spectrum boundaries. The resolution values obtained were about twice higher than those predicted by peripheral auditory filter tuning.

Evidence of across-channel processing for spectral-ripple discrimination in cochlear implant listeners

“…Spectral-ripple discrimination, originally developed to investigate the spectral resolution of the normal auditory system (e.g., Supin et al, 1994Supin et al, , 1998Supin et al, , 1999, has recently gained a wide range of attention in the cochlear implant (CI) research field (e.g., Henry and Turner, 2003;Henry et al, 2005;Won et al, 2007;Litvak et al, 2007;Saoji et al, 2009;Drennan et al, 2010;Won et al, 2010Won et al, , 2011Anderson et al, 2011). These previous studies demonstrated that spectral-ripple discrimination correlates with vowel and consonant recognition in quiet (Henry et al, 2003(Henry et al, , 2005Saoji et al, 2009), speech perception in noise (Won et al, 2007), and music perception .…”

Masking of rippled-spectrum-pattern resolution in diotic and dichotic presentations

“…Its special versions (including ''iterated rippled noise") with equally spaced ripples were also successfully used to investigate the time-separation pitch effect Yost andHill, 1978, 1979;Bilsen and Wieman, 1980;Yost, 1982). However, in later investigations of spectrum-pattern discrimination, frequency-proportional ripple patterns were used as better fitting the frequency representation in the cochlea (Supin et al, 1998(Supin et al, , 1999Eddins and Bero, 2007). To some extent, this approach is close to the spectrum profile analysis proposed by Green (1986Green ( , 1987; it, however, uses both ripple depth and density to characterize the spectrum-pattern resolution.…”

Rippled spectrum discrimination in noise: Effects of compression

“…The equivalent rectangular bandwidth (ERB) of this band is 0.38 octaves. The cosine envelope was used to avoid effects from sharp spectrum edges, which might influence the resolution of the ripple patterns (Supin et al, 1998). Within the cosine envelope, ripples were defined by a cosine function of the logarithm of frequency, as shown in Fig.…”

“…Apart from primary spectrum structure (center frequency, shape, and bandwidth), rippled spectra feature a secondary structure: ripple shape, depth, and density within the spectrum envelope. The resolution of rippled spectra in normal listeners was investigated in several previous studies (Supin et al, 1994(Supin et al, , 1998(Supin et al, , 1999Nechaev and Supin, 2013;Aronoff and Landsberger, 2013). It has been demonstrated that both on-and low-frequency maskers deteriorate the resolution of the second rippledspectrum structure (Supin et al, 2001(Supin et al, , 2003Nechaev et al, 2015).…”