The relative importance of spectral cues for vowel recognition in severe noise

Abstract

The importance of formants and spectral shape was investigated for vowel perception in severe noise. Twelve vowels were synthesized using two different synthesis methods, one where the original spectral detail was preserved, and one where the vowel was represented by the spectral peaks of the first three formants. In addition, formants F1 and F2 were suppressed individually to investigate the importance of each in severe noise. Vowels were presented to listeners in quiet and in speechshaped noise at signal to noise ratios (SNRs) of 0, À5, and À10 dB, and vowel confusions were determined in a number of conditions. Results suggest that the auditory system relies on formant information for vowel perception irrespective of the SNR, but that, as noise increases, it relies increasingly on more complete spectral information to perform formant extraction. A second finding was that, while F2 is more important in quiet or low noise conditions, F1 and F2 are of similar importance in severe noise.

Identification of high-pass filtered male, female, and child vowels: The use of high-frequency cues

“…Vowels are characteristically described according to low-frequency resonance characteristics (e.g., Peterson and Barney, 1952;Hillenbrand et al, 1995;Molis, 2005;Swanepoel et al, 2012). Classically, the study of vowel perception has focused on the lowest formant frequencies, typically F1, F2, and F3.…”

Contribution of formant frequency information to vowel perception in steady-state noise by cochlear implant users

“…Alternatively, it is possible that the speech cues employed in the present study, i.e., formant energy locations along the implanted array, may not be as predictive of CI users' vowel confusions in noise as they are in quiet. Normal hearing listeners can utilize a large number of acoustic cues when identifying speech sounds, and the particular cues they employ in quiet listening conditions may not be the same as the cues they employ in noisy listening conditions (Ferguson and Kewley-Port, 2002;Parikh and Loizou, 2005;Swanepoel et al, 2012). Although CI users are more limited in the number and type of speech cues they can employ to understand speech, the speech cues they use to understand speech in noise may differ than those used for quiet.…”

“…It is possible to incorporate relative weighting between speech cue dimensions, particularly in the decision component of the model. Given that listeners with normal hearing can utilize different perceptual weighting of speech cues when understanding speech in noise in comparison to quiet (Ferguson and Kewley-Port, 2002;Parikh and Loizou, 2005;Swanepoel et al, 2012), it may be worthwhile to explore this ability in CI users. Last, the present study offers an immediate practical application.…”

“…In the presence of background noise, listeners with normal hearing maintain their reliance on these cues to identify vowels, although at very low SNRs there may be a shift in the relative perceptual weighting assigned to these cues (Ferguson and Kewley-Port, 2002;Parikh and Loizou, 2005;Swanepoel et al, 2012). CI listeners use similar speech cues as listeners with normal hearing to identify vowels in quiet, although with different efficiency and perceptual weighting between cues, including steady-state and dynamic formant information as well as vowel duration (Donaldson et al, 2013(Donaldson et al, , 2015Iverson et al, 2006;Kirk et al, 1992;Sagi et al, 2010b;Winn et al, 2012).…”

Perceptual Information Loss due to Impaired Speech Production

“…The limitation of the binary association is that it requires detection of the attributes by human subjects, and measurement of the degree an attribute is present is not feasible [23], [27]. In contrast to the binary mapping, in practice a complex function governs the phonetic-phonological association that motivates the use of advanced computational methods for probabilistic characterization.…”