Unsupervised visualization of Under-resourced speech prosody
Publication date: July 2018Source: Speech Communication, Volume 101Author(s): Moses Ekpenyong, Udoinyang Inyang, EmemObong UdohAbstractIn this paper, an unsupervised visualization framework for analyzing under-resourced speech prosody is proposed. An experiment was carried out for Ibibio–a Lower Cross Language of the New Benue Congo family, spoken in the Southeast coastal region of Nigeria, West Africa. The proposed methodology adopts machine learning, with semi-automated procedure for extracting prosodic features from a translated prosodically stable corpus ‘The Tiger and the Mouse’—a text corpus that demonstrates...
Source: Speech Communication - July 5, 2018 Category: Speech-Language Pathology Source Type: research
Where has all the power gone? Energy production and loss in vocalization
Publication date: July 2018Source: Speech Communication, Volume 101Author(s): Ingo R. TitzeAbstractHuman voice production for speech is an inefficient process in terms of energy expended to produce acoustic output. A traditional measure of vocal efficiency relates acoustic power radiated from the mouth to aerodynamic power produced in the trachea. This efficiency ranges between 0.001% and 1.0% in speech-like vocalization. Simplified Navier–Stokes equations for non-steady compressible airflow from trachea to lips were used to calculate steady aerodynamic power, acoustic power, and combined total power at seven strategic l...
Source: Speech Communication - July 5, 2018 Category: Speech-Language Pathology Source Type: research
Speech enhancement in spectral envelop and details subspaces
In this study, we address this challenge through a combination strategy of spectral modulation decoupling and low-rank and sparsity oriented decomposition. Specifically, supervised low-rank and sparse decompositions with energy thresholding are developed in the spectral envelop subspace, In the spectral details subspace, an unsupervised robust principal component analysis is utilized to extract the fine structure. The validation results show that, compared with five speech enhancement algorithms, including MMSE-SPP, NMF-RPCA, RPCA, LARC and BNMF, the proposed algorithms achieves satisfactory performance on improving both p...
Source: Speech Communication - July 5, 2018 Category: Speech-Language Pathology Source Type: research
Speaker models for monitoring Parkinson’s disease progression considering different communication channels and acoustic conditions
Publication date: July 2018Source: Speech Communication, Volume 101Author(s): T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, E. NöthAbstractSymptoms of Parkinson’s disease vary from patient to patient. Additionally, the progression of those symptoms also differs among patients. Most of the studies on the analysis of speech of people with Parkinson’s disease do not consider such an individual variation. This paper presents a methodology for the automatic and individual monitoring of speech disorders developed by PD patients. The neurological state and dysarthria level of the patients are evaluated. The p...
Source: Speech Communication - July 5, 2018 Category: Speech-Language Pathology Source Type: research
Influence of visual cues on head and eye movements during listening tasks in multi-talker audiovisual environments with animated characters
Publication date: July 2018Source: Speech Communication, Volume 101Author(s): Maartje M.E. Hendrikse, Gerard Llorach, Giso Grimm, Volker HohmannAbstractRecent studies of hearing aid benefits indicate that head movement behavior influences performance. To systematically assess these effects, movement behavior must be measured in realistic communication conditions. For this, the use of virtual audiovisual environments with animated characters as visual stimuli has been proposed. It is unclear, however, how these animations influence the head- and eye-movement behavior of subjects. Here, two listening tasks were carried out w...
Source: Speech Communication - July 5, 2018 Category: Speech-Language Pathology Source Type: research
