This study aims to test a prediction of recent theoretical frameworks in speech motor control: if speech production targets are specified in auditory terms, people with better auditory acuity should have more precise speech targets. To investigate this, we had participants perform speech perception and production tasks in a counterbalanced order. To assess speech perception acuity, we used an a...

Alternative assessment approaches received considerable attention soon after a discontent with traditional, one-shot testing. These approaches, however, have been used only to improve learners’ linguistic ability despite communicative models of language which pointed that knowledge of language also involves pragmatic ability (Bachman, 1990; Bachman & Palmer, 1996). The present study tries to ex...

We propose a spectro-temporal regularization approach for NMF that accounts for a source’s spectral variability over time. The regularization terms allow NMF to adapt the spectral basis matrices optimally to reduce mismatch between the spectral characteristics of sources observed during training and encountered during separation. We first tested our algorithm on a simulated source separation ta...

We present a novel method for extracting target speech from auditory mixtures using bimodal coherence, which is statistically characterised by a Gaussian mixture modal (GMM) in the offline training process, using the robust features obtained from the audio-visual speech. We then adjust the ICA-separated spectral components using the bimodal coherence in the time-frequency domain, to mitigate th...

This study assesses the methane production potential for Anaerobic Digestion of Pig Slurry, using two different Substrate to Inoculum Ratios, 0.65, and 1, its comparison with theoretical prediction. The Specific Biogas Production, Methane average content were determined both experiments adjusted Standard Temperature (273.15 K) Pressure (1 atm). results reached in this show that experience condu...

For separating multiple speech signals given a convolutive mixture, time-frequency sparseness of the speech sources can be exploited. In this paper we present a multi-channel source separation method based on the concept of approximate disjoint orthogonality of speech signals. Unlike binary masking of singlechannel signals as e.g. applied in the DUET algorithm we use a likelihood mask to contro...