Missing-data model of vowel identification

Cheveigné, Alain de; Kawahara, Hideki

doi:10.1121/1.424675

Cited by 41 publications

(13 citation statements)

References 53 publications

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“…As to the possibility of signal distortion, Miller et al (2010) proposed the explanation that when the synthesized f0 is considerably higher than the original f0, the formant peaks of the vowels are reduced due to misalignment of harmonics of f0 with vocal-tract resonances (de Cheveigné & Kawahara, 1999;Diehl, Lindblom, Hoemeke, & Fahey, 1996). This distortion could lower speech intelligibility, particularly in background noise.…”

Section: Discussionmentioning

confidence: 99%

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

Shen

Souza

2017

J Speech Lang Hear Res

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Purpose This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Method Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. Results The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Conclusions Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss.

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Section: Discussionmentioning

confidence: 99%

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

Shen

Souza

2017

J Speech Lang Hear Res

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“…Human listeners are little affected by large changes in F0 despite the sparse sampling at higher F0's (e.g., Assmann and Katz, 2000). One promising approach is the "missing information" matching of spectral templates, in which only frequencies at which a harmonic is present contribute to the output (de Cheveign e and Kawahara, 1999). In this way, entire formants can be unrepresented by harmonics, but their absence does not affect identification rates.…”

Section: Discussionmentioning

confidence: 99%

Comparing measurement errors for formants in synthetic and natural vowels

Shadle

Nam

Whalen

2016

The Journal of the Acoustical Society of America

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The measurement of formant frequencies of vowels is among the most common measurements in speech studies, but measurements are known to be biased by the particular fundamental frequency (F0) exciting the formants. Approaches to reducing the errors were assessed in two experiments. In the first, synthetic vowels were constructed with five different first formant (F1) values and nine different F0 values; formant bandwidths, and higher formant frequencies, were constant. Input formant values were compared to manual measurements and automatic measures using the linear prediction coding-Burg algorithm, linear prediction closed-phase covariance, the weighted linear prediction-attenuated main excitation (WLP-AME) algorithm [Alku, Pohjalainen, Vainio, Laukkanen, and Story (2013). J. Acoust. Soc. Am. 134(2), 1295-1313], spectra smoothed cepstrally and by averaging repeated discrete Fourier transforms. Formants were also measured manually from pruned reassigned spectrograms (RSs) [Fulop (2011). Speech Spectrum Analysis (Springer, Berlin)]. All but WLP-AME and RS had large errors in the direction of the strongest harmonic; the smallest errors occur with WLP-AME and RS. In the second experiment, these methods were used on vowels in isolated words spoken by four speakers. Results for the natural speech show that F0 bias affects all automatic methods, including WLP-AME; only the formants measured manually from RS appeared to be accurate. In addition, RS coped better with weaker formants and glottal fry.

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“…Thus, the optimal resolution for vowel quality perception may be found in the low-spectral-, high-temporal-resolution channel rather than the high-spectral-, lowtemporal-resolution channel ͑but cf. Cheveigné and Kawahara, 1999;Hillenbrand and Houde, 2003͒. A number of behavioral methods could be used to experimentally test the temporal resolution of vowel quality perception. Past research has investigated vowel perception by measuring the temporal limits of forward and backward masking.…”

Section: Introductionmentioning

confidence: 99%

Temporal integration in vowel perception

Wallace

Blumstein

2009

The Journal of the Acoustical Society of America

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Psychoacoustic research suggests that multiple auditory channels process incoming sounds over temporal windows of different durations, resulting in multiple auditory representations being available to higher-level processes. The current experiments investigate the size of the temporal window used in vowel quality perception using an acoustic priming paradigm with nonspeech and speech primes of varying duration. In experiment 1, identification of vowel targets was facilitated by acoustically matched nonspeech primes. The magnitude of this effect was greatest for the shortest ͑25 and 50 ms͒ primes, remained level at medium ͑100 and 150 ms͒ duration primes, and declined significantly at longer prime durations, suggesting that the auditory stages of vowel quality perception integrate sensory input over a relatively short temporal window. In experiment 2, the same vowel targets were primed by speech stimuli, consisting of vowels using the same duration values as those in experiment 1. A different pattern of results emerged with the greatest priming effects found for primes of around 150 ms and less priming at the shorter and longer durations, indicating that longer-scale temporal processes operate at higher levels of analysis.

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Missing-data model of vowel identification

Cited by 41 publications

References 53 publications

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

Comparing measurement errors for formants in synthetic and natural vowels

Temporal integration in vowel perception

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