Speech recognition performance was measured in normal-hearing and cochlear-implant listeners with maskers consisting of either steady-state speech-spectrum-shaped noise or a competing sentence. Target sentences from a male talker were presented in the presence of one of three competing talkers (same male, different male, or female) or speech-spectrum-shaped noise generated from this talker at several target-to-masker ratios. For the normal-hearing listeners, target-masker combinations were processed through a noise-excited vocoder designed to simulate a cochlear implant. With unprocessed stimuli, a normal-hearing control group maintained high levels of intelligibility down to target-to-masker ratios as low as 0 dB and showed a release from masking, producing better performance with single-talker maskers than with steady-state noise. In contrast, no masking release was observed in either implant or normal-hearing subjects listening through an implant simulation. The performance of the simulation and implant groups did not improve when the single-talker masker was a different talker compared to the same talker as the target speech, as was found in the normal-hearing control. These results are interpreted as evidence for a significant role of informational masking and modulation interference in cochlear implant speech recognition with fluctuating maskers. This informational masking may originate from increased target-masker similarity when spectral resolution is reduced.

If two vowels with different fundamental frequencies (fo's) are presented simultaneously and monaurally, listeners often hear two talkers producing different vowels on different pitches. This paper describes the evaluation of four computational models of the auditory and perceptual processes which may underlie this ability. Each model involves four stages: (i) frequency analysis using an "auditory" filter bank, (ii) determination of the pitches present in the stimulus, (iii) segregation of the competing speech sources by grouping energy associated with each pitch to create two derived spectral patterns, and (iv) classification of the derived spectral patterns to predict the probabilities of listeners' vowel-identification responses. The "place" models carry out the operations of pitch determination and spectral segregation by analyzing the distribution of rms levels across the channels of the filter bank. The "place-time" models carry out these operations by analyzing the periodicities in the waveforms in each channel. In their "linear" versions, the place and place-time models operate directly on the waveforms emerging from the filters. In their "nonlinear" versions, analogous operations are applied to the output of an additional stage which applied a compressive nonlinearity to the filtered waveforms. Compared to the other three models, the nonlinear place-time model provides the most accurate estimates of the fo's of paris of concurrent synthetic vowels and comes closest to predicting the identification responses of listeners to such stimuli. Although the model has several limitations, the results are compatible with the idea that a place-time analysis is used to segregate competing sound sources.

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Statistical analysis of F1 and F2 measurements from nucleus and offglide sections of isolated Canadian English vowels shows significant formant frequency change not only for the ‘‘phonetic diphthongs’’ /e/ and /o/, but also for the ‘‘monophthongs’’ /ι/, /q/, and /1/. In a perceptual experiment, brief sections were extracted from ‘‘nucleus’’ and ‘‘offglide’’ portions of naturally produced vowels. Two sections from each vowel were presented to listeners in each of three conditions: (1) natural order (nucleus followed by offglide); (2) repeated nucleus (nucleus followed by itself); and (3) reverse (offglide followed by nucleus). Listeners’ error rates for the natural order condition were comparable to those for unmodified full vowels (averaging 14% and 13%, respectively). Significantly higher error rates were found for the repeated nucleus (32%) and reverse (38%) conditions. Observed confusion matrices were strongly correlated with predictions from a pattern recognition model incorporating the formant measurements. This study provides evidence for the importance of inherent spectral change in listeners’ perception of isolated vowels. In addition, the problem of the parametric representation of formant trajectories is discussed and preliminary evidence for the persistence of vowel-inherent spectral change in consonantal context is presented.

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.