Sentence examples for spectral voice from inspiring English sources

Hunched over his guitar, Johnson sang into a corner of the room, unleashing his spectral voice.

We now use the GB approximation method described above as a framework for spectral voice conversion.

In my case, the technology is a $20 program produced by a company called atOnce Software and featuring sound effects that include a spectral voice telling you when you've been checked;rather helpful for patzers.

The sound generation system is based on a parametric synthesizer that features a spectral voice source model, a vocal tract model consisting of parallel filters for vocalic formants and cascaded with anti-resonance for the spectral effect of hypo-pharynx cavities, and rules for parameter settings and source/filter dependencies between fundamental frequency, vocal effort, and formants.

"The Ghost Writer," Harwood's first novel, is an echo chamber of spectral voices, some emanating from within his tricky, booby-trapped plot and some, more faintly, from without.

max Table 3 Structure of the feature set P3 Number Name Type Frame Value 1 HNR Complementary spectral Voiced Mean 2 HNR Complementary spectral Voiced Std 3 HNR Complementary spectral Voiced Rel.

max 4 SC Complementary spectral Voiced Mean 5 SC Complementary spectral Voiced Std 6 SFM Complementary spectral Voiced Mean 7 SFM Complementary spectral Voiced Std 8 SE Complementary spectral All Mean 9 SE Complementary spectral All Std 10 F0 Supra-segmental Voiced Median 11 F0 Supra-segmental Voiced Std 12 F0DIFF Supra-segmental Voiced Rel.

c3 Basic spectral All Kurtosis 7 SC Complementary spectral Voiced Mean 8 SC Complementary spectral Voiced Std 9 SFM Complementary spectral Voiced Mean 10 SFM Complementary spectral Voiced Std 11 SE Complementary spectral All Mean 12 SE Complementary spectral All Std 13 F0 Supra-segmental Voiced Median 14 F0 DIFF Supra-segmental Voiced Rel.

Specifically, we extracted prosodic, spectral, and voice quality features to capture global acoustic properties for each spouse and trained gender-specific and gender-independent classifiers.

Likewise, in loud environments, the Lombard effect [42] changes the speech pattern of a person and makes it in many acoustic parameters (F0, speaking rate, spectral tilt, voice quality) very similar to the characteristic settings of anger or rage [43].

Pressure on the stylus controls the vocal effort, the main influence of which is to change the voice spectral tilt.