The Journal of the Acoustical Society of America
-
J. Acoust. Soc. Am. · Apr 2021
Click evoked middle ear muscle reflex: Spectral and temporal aspects.
This study describes a time series-based method of middle ear muscle reflex (MEMR) detection using bilateral clicks. Although many methods can detect changes in the otoacoustic emissions evoking stimulus to monitor the MEMR, they do not discriminate between true MEMR-mediated vs artifactual changes in the stimulus. We measured MEMR in 20 young clinically normal hearing individuals using 1-s-long click trains presented at six levels (65 to 95 dB peak-to-peak sound pressure level in 6 dB steps). ⋯ MEMR thresholds estimated using this method were lower than that obtained from a clinical tympanometer in ∼94% of the participants. A time series-based method, along with statistical tests, may provide additional confidence in detecting the MEMR. MEMR effects were smallest at 2 kHz, between 1 and 3.2 kHz, which may provide avenues for minimizing the MEMR influence while measuring other responses (e.g., the medial olivocochlear reflex).
-
J. Acoust. Soc. Am. · Dec 2020
Effects of face masks on acoustic analysis and speech perception: Implications for peri-pandemic protocols.
Wearing face masks (alongside physical distancing) provides some protection against infection from COVID-19. Face masks can also change how people communicate and subsequently affect speech signal quality. This study investigated how three common face mask types (N95, surgical, and cloth) affected acoustic analysis of speech and perceived intelligibility in healthy subjects. ⋯ No differences were observed across conditions for word or sentence intelligibility measures; however, accuracy of word and sentence translations were affected by all masks. Data presented in this study show that face masks change the speech signal, but some specific acoustic features remain largely unaffected (e.g., measures of voice quality) irrespective of mask type. Outcomes have bearing on how future speech studies are run when personal protective equipment is worn.
-
With the COVID-19 pandemic, the wearing of face masks covering mouth and nose has become ubiquitous all around the world. This study investigates the impact of typical face masks on voice radiation. To analyze the transmission loss caused by masks and the influence of masks on directivity, this study measured the full-spherical voice directivity of a dummy head with a mouth simulator covered with six masks of different types, i.e., medical masks, filtering facepiece respirator masks, and cloth face coverings. ⋯ Furthermore, the two facepiece respirator masks also significantly affect speech directivity, as determined by the directivity index (DI). Compared to the measurements without a mask, the DI deviates by up to 7 dB at frequencies above 3 kHz. For all other masks, the deviations are below 2 dB in all third-octave frequency bands.
-
J. Acoust. Soc. Am. · Nov 2019
Acoustic and linguistic factors affecting perceptual dissimilarity judgments of voices.
The human voice is a complex acoustic signal that conveys talker identity via individual differences in numerous features, including vocal source acoustics, vocal tract resonances, and dynamic articulations during speech. It remains poorly understood how differences in these features contribute to perceptual dissimilarity of voices and, moreover, whether linguistic differences between listeners and talkers interact during perceptual judgments of voices. Here, native English- and Mandarin-speaking listeners rated the perceptual dissimilarity of voices speaking English or Mandarin from either forward or time-reversed speech. ⋯ Representational similarity analyses that explored how acoustic features (fundamental frequency mean and variation, jitter, harmonics-to-noise ratio, speech rate, and formant dispersion) contributed to listeners' perceptual dissimilarity judgments, including how talker- and listener-language affected these relationships, found the largest effects relating to voice pitch. Overall, these data suggest that, while linguistic factors may influence perceptual judgments of voices, the magnitude of such effects tends to be very small. Perceptual judgments of voices by listeners of different native language backgrounds tend to be more alike than different.
-
J. Acoust. Soc. Am. · Sep 2018
A deep learning based segregation algorithm to increase speech intelligibility for hearing-impaired listeners in reverberant-noisy conditions.
Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The combination of reverberation and background noise can severely degrade speech intelligibility for hearing-impaired (HI) listeners. ⋯ The algorithm was also somewhat beneficial for normal-hearing (NH) listeners. In addition, sentence intelligibility scores for HI listeners with algorithm processing approached or matched those of young-adult NH listeners without processing. The current study represents a step toward deploying deep learning algorithms to help the speech understanding of HI listeners in everyday conditions.