Consonant identification using temporal fine structure and recovered envelope cues

Swaminathan, Jaichander; Reed, Charlotte M.; Desloge, Joseph G.; Braida, Louis D.; Delhorne, Lorraine A.

doi:10.1121/1.4865920

Cited by 12 publications

(22 citation statements)

References 46 publications

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“…Consistent with other studies (Gilbert and Lorenzi, 2006;Swaminathan, 2010;Lorenzi et al, 2012;Swaminathan et al, 2014;L eger et al, 2015), our results suggest that the reception of TFS speech is based on the use of RENVs for both NH and HI listeners. In the current study, the reception of one-band and four-band TFS speech was compared to speech signals created through the extraction of 40 bands of ENVs from each type of TFS speech.…”

Section: Role Of Renvs In Perception Of Tfs Speechsupporting

confidence: 81%

“…The high degree of resolution in extracting the recovered envelopes (40 bands) may have contributed to the similarity in scores between T and R speech. However, previous results (Swaminathan et al, 2014) indicate that the use of fewer bands (e.g., 32 instead of 40) would have only led to a slight decrease in performance for R speech. Referring to Fig.…”

Section: Role Of Renvs In Perception Of Tfs Speechmentioning

confidence: 67%

“…The speech conditions were tested in the order of U, T1, R1, T4, R4, and E. This order was chosen to optimize training based on Swaminathan et al (2014). For each speech condition, performance was measured first for the baseline condition and then with the continuous and interrupted noise in random order.…”

Section: Methodsmentioning

confidence: 99%

“…Overall performance decreased with an increase in the width of the analysis filters used to create the RENV speech. Swaminathan et al (2014) used a similar approach to creating RENV signals from TFS speech as that of Gilbert and Lorenzi (2006), but filtered the TFS speech into 40 rather than 30 bands for ENV extraction over the same frequency range. [Their use of 40 bands was based on results of Shera et al (2002), suggesting that human auditory filters are sharper than standard behavioral measures.]…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Consonant identification in noise using Hilbert-transform temporal fine-structure speech and recovered-envelope speech for listeners with normal and impaired hearing

Léger

Reed

Desloge

et al. 2015

The Journal of the Acoustical Society of America

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Consonant-identification ability was examined in normal-hearing (NH) and hearing-impaired (HI) listeners in the presence of steady-state and 10-Hz square-wave interrupted speech-shaped noise. The Hilbert transform was used to process speech stimuli (16 consonants in a-C-a syllables) to present envelope cues, temporal fine-structure (TFS) cues, or envelope cues recovered from TFS speech. The performance of the HI listeners was inferior to that of the NH listeners both in terms of lower levels of performance in the baseline condition and in the need for higher signal-to-noise ratio to yield a given level of performance. For NH listeners, scores were higher in interrupted noise than in steady-state noise for all speech types (indicating substantial masking release). For HI listeners, masking release was typically observed for TFS and recovered-envelope speech but not for unprocessed and envelope speech. For both groups of listeners, TFS and recovered-envelope speech yielded similar levels of performance and consonant confusion patterns. The masking release observed for TFS and recovered-envelope speech may be related to level effects associated with the manner in which the TFS processing interacts with the interrupted noise signal, rather than to the contributions of TFS cues per se.

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Section: Role Of Renvs In Perception Of Tfs Speechsupporting

confidence: 81%

Section: Role Of Renvs In Perception Of Tfs Speechmentioning

confidence: 67%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Consonant identification in noise using Hilbert-transform temporal fine-structure speech and recovered-envelope speech for listeners with normal and impaired hearing

Léger

Reed

Desloge

et al. 2015

The Journal of the Acoustical Society of America

Self Cite

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“…The first stage of processing generates the 40-band E signal described above, which consists of 40 amplitude-modulated sine waves with random starting phases. Randomizing the starting phases of the 40 tones that are modulated to generate the E signal yields random TFS cues that are unrelated to those of the original stimulus (as confirmed by Swaminathan et al, 2014). 3 For the second stage of processing, the E speech was reprocessed with broadband Hilbert transform TFS (i.e., T1) processing to remove amplitude variation yielding E/T1 speech.…”

Section: Processing Conditionsmentioning

confidence: 99%

Level variations in speech: Effect on masking release in hearing-impaired listeners

Reed

Desloge

Braida

et al. 2016

The Journal of the Acoustical Society of America

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Acoustic speech is marked by time-varying changes in the amplitude envelope that may pose difficulties for hearing-impaired listeners. Removal of these variations (e.g., by the Hilbert transform) could improve speech reception for such listeners, particularly in fluctuating interference. Léger, Reed, Desloge, Swaminathan, and Braida [(2015b). J. Acoust. Soc. Am. 138, 389–403] observed that a normalized measure of masking release obtained for hearing-impaired listeners using speech processed to preserve temporal fine-structure (TFS) cues was larger than that for unprocessed or envelope-based speech. This study measured masking release for two other speech signals in which level variations were minimal: peak clipping and TFS processing of an envelope signal. Consonant identification was measured for hearing-impaired listeners in backgrounds of continuous and fluctuating speech-shaped noise. The normalized masking release obtained using speech with normal variations in overall level was substantially less than that observed using speech processed to achieve highly restricted level variations. These results suggest that the performance of hearing-impaired listeners in fluctuating noise may be improved by signal processing that leads to a decrease in stimulus level variations.

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Predictions of Speech Chimaera Intelligibility Using Auditory Nerve Mean-Rate and Spike-Timing Neural Cues

Wirtzfeld

Ibrahim

Bruce

2017

JARO

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Perceptual studies of speech intelligibility have shown that slow variations of acoustic envelope (ENV) in a small set of frequency bands provides adequate information for good perceptual performance in quiet, whereas acoustic temporal fine-structure (TFS) cues play a supporting role in background noise. However, the implications for neural coding are prone to misinterpretation because the mean-rate neural representation can contain recovered ENV cues from cochlear filtering of TFS. We investigated ENV recovery and spike-time TFS coding using objective measures of simulated mean-rate and spike-timing neural representations of chimaeric speech, in which either the ENV or the TFS is replaced by another signal. We (a) evaluated the levels of mean-rate and spike-timing neural information for two categories of chimaeric speech, one retaining ENV cues and the other TFS; (b) examined the level of recovered ENV from cochlear filtering of TFS speech; (c) examined and quantified the contribution to recovered ENV from spike-timing cues using a lateral inhibition network (LIN); and (d) constructed linear regression models with objective measures of mean-rate and spike-timing neural cues and subjective phoneme perception scores from normal-hearing listeners. The mean-rate neural cues from the original ENV and recovered ENV partially accounted for perceptual score variability, with additional variability explained by the recovered ENV from the LIN-processed TFS speech. The best model predictions of chimaeric speech intelligibility were found when both the mean-rate and spike-timing neural cues were included, providing further evidence that spike-time coding of TFS cues is important for intelligibility when the speech envelope is degraded.

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Consonant identification using temporal fine structure and recovered envelope cues

Cited by 12 publications

References 46 publications

Consonant identification in noise using Hilbert-transform temporal fine-structure speech and recovered-envelope speech for listeners with normal and impaired hearing

Consonant identification in noise using Hilbert-transform temporal fine-structure speech and recovered-envelope speech for listeners with normal and impaired hearing

Level variations in speech: Effect on masking release in hearing-impaired listeners

Predictions of Speech Chimaera Intelligibility Using Auditory Nerve Mean-Rate and Spike-Timing Neural Cues

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