Effects of cochlear implant processing and fundamental frequency on the intelligibility of competing sentences

Abstract

Speech perception in the presence of another competing voice is one of the most challenging tasks for cochlear implant users. Several studies have shown that (1) the fundamental frequency (F0) is a useful cue for segregating competing speech sounds and (2) the F0 is better represented by the temporal fine structure than by the temporal envelope. However, current cochlear implant speech processing algorithms emphasize temporal envelope information and discard the temporal fine structure. In this study, speech recognition was measured as a function of the F0 separation of the target and competing sentence in normal-hearing and cochlear implant listeners. For the normal-hearing listeners, the combined sentences were processed through either a standard implant simulation or a new algorithm which additionally extracts a slowed-down version of the temporal fine structure (called Frequency-Amplitude-Modulation-Encoding). The results showed no benefit of increasing F0 separation for the cochlear implant or simulation groups. In contrast, the new algorithm resulted in gradual improvements with increasing F0 separation, similar to that found with unprocessed sentences. These results emphasize the importance of temporal fine structure for speech perception and demonstrate a potential remedy for difficulty in the perceptual segregation of competing speech sounds.

Role of binaural hearing in speech intelligibility and spatial release from masking using vocoded speech

“…However, amount of masking was comparable for the three frequency band conditions ͑16, 8, and 4͒ suggesting that once speech is spectrally degraded, the susceptibility to masking is relatively high. In line with previous studies, current results underscore the limitation of CI vocoders in reproducing the fine structure information which is known to be important in speech recognition, particularly in the presence of temporally overlapping speech sounds ͑e.g., Smith et al, 2002;Stickney et al, , 2007Rubinstein and Hong, 2003;Wilson et al, 2003. These results further suggest that when finestructure information is reduced by vocoding, increasing the number of bands might not be the most constructive solution to the problem.…”

Effect of fundamental-frequency and sentence-onset differences on speech-identification performance of young and older adults in a competing-talker background

“…The STRAIGHT program estimated the F0 contour of each of the 256 sentences spoken by T1 in a 1-ms frame and then resynthesized the F0 contour to be shifted corresponding to the target amount of DF0. The STRAIGHT MATLAB code has been used to modify the average F0 of sentences in recent studies because STRAIGHT is known to successfully shift F0 while preserving the natural pattern of the F0 contour in the target sentence without evoking much change in the formants (Carroll and Zeng, 2007;Stickney et al, 2007). For conditions with a DF0 of 0 ST, the F0 contours of both target and competing sentences were not processed.…”

Modulation Frequency Discrimination with Modulated and Unmodulated Interference in Normal Hearing and in Cochlear-Implant Users

“…Therefore, a potentially important factor in explaining this deficit is the relatively poor pitch perception of most CI users. The loss of pitch information may be in part due to poorer spectral resolution (caused by a limited number of electrodes, non-uniform survival of spiral ganglion cells, and spread of current) and to the loss of temporal fine structure information within individual frequency channels, which in turn may impede speech perception in complex backgrounds (e.g., Qin and Oxenham 2003;Stickney et al 2007).…”