Sentence examples for speech acoustic from inspiring English sources

Sehr et al. [17] suggest to adapt the output probability density function of the clean speech acoustic model to the reverberant condition in the decoding stage.

A small set of evaluative criteria for these measures is presented first, followed by consideration of several speech physiology and speech acoustic measures that have been studied frequently and reported on in the literature on normal speech production, and speech production affected by neuromotor disorders (dysarthria).

Such environments, for example domestic and multi-room offices, present challenging acoustic scenes to state-of-the-art speech recognizers, especially under always-listening operation, due to low signal-to-noise ratios, frequent overlaps of target speech, acoustic events, and background noise, as well as inter-room interference and reverberation.

Recently, a major advance has been made in using deep neural networks (DNNs) with many hidden layers for speech acoustic modeling, where the resulting DNNs learn a hierarchy of nonlinear feature detectors that can capture complex statistical patterns for speech data.

Specifically, we have demonstrated that children monitor spectral properties of their speech acoustic signal, making compensatory motor adjustments when necessary to maintain accuracy.

All subjects carried out the following sequence of tasks: Acclimatization: Subjects read aloud a sequence of 90 words into a microphone while listening to their amplified, but otherwise unaltered, speech acoustic signal through headphones (SR-80, Grado Labs, Brooklyn, NY).

In addition to natural language processing (NLP) features, speech acoustics have also been studied and reported in the literature.

We were able to dissociate auditory and somatosensory feedback by using a robotic device that altered the jaw's motion path, and hence proprioception, without affecting speech acoustics.

The visual signal is presented in synchrony with the acoustic speech signal, which means that the user can benefit from the combined synchronised audiovisual perception of the original speech acoustics and the resynthesised visible articulation.

The early-stage Bachelor students were naive insofar as none them had taken part in a perception experiment before nor had anyone of them enrolled for lectures in prosody or speech acoustics.

Spectro-temporal signal analysis has been shown useful in other physiological domains, such as heart and lung sound separation [38], pulmonary adventitious sound analysis [39], dysphonia recognition [40], and speech acoustics analysis [41].