Uso de equações de diferenças na obtenção de filtros para redução de ruído em sinais de voz no domínio wavelet

Pós-graduação em Engenharia Elétrica - FEIS

Estudo e implementação de uma técnica de redução de ruído em sinais de voz baseada na subtração espectral e em critérios psicoacústicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito da fase em técnicas de redução de ruídos em sinais de voz baseadas na SNR a priori

Pós-graduação em Engenharia Elétrica - FEIS

Benefit of a Contralateral Routing of Signal Device for Unilateral Cochlear Implant Users.

Objective: To investigate objective and subjective effects of an adjunctive contralateral routing of signal (CROS) device at the untreated ear in patients with a unilateral cochlear implant (CI). Design: Prospective study of 10 adult experienced unilateral CI users with bilateral severe-to-profound hearing loss. Speech in noise reception (SNR) and sound localization were measured with and without the additional CROS device. SNR was measured by applying speech signals at the untreated/CROS side while noise signals came from the front (S90N0). For S0N90, signal sources were switched. Sound localization was measured in a 12-loudspeaker full circle setup. To evaluate the subjective benefit, patients tried the device for 2 weeks at home, then filled out the abbreviated Speech, Spatial and Qualities of Hearing Scale as well as the Bern benefit in single-sided deafness questionnaires. Results: In the setting S90N0, all patients showed a highly significant SNR improvement when wearing the additional CROS device (mean 6.4 dB, p < 0.001). In the unfavorable setting S0N90, only a minor deterioration of speech understanding was noted (mean -0.66 dB, p = 0.54). Sound localization did not improve substantially with CROS. In the two questionnaires, 12 of 14 items showed an improvement in mean values, but none of them was statistically significant. Conclusion: Patients with unilateral CI benefit from a contralateral CROS device, particularly in a noisy environment, when speech comes from the CROS ear side. © 2014 S. Karger AG, Basel.

Automatic control of attenuation in a digital communication network

This thesis describes the investigation of an adaptive method of attenuation control for digital speech signals in an analogue-digital environment and its effects on the transmission performance of a national telecommunication network. The first part gives the design of a digital automatic gain control, able to operate upon a P.C.M. signal in its companded form and whose operation is based upon the counting of peaks of the digital speech signal above certain threshold levels. A study was ma.de of a digital automatic gain control (d.a.g.c.) in open-loop configuration and closed-loop configuration. The former was adopted as the means for carrying out the automatic control of attenuation. It was simulated and tested, both objectively and subjectively. The final part is the assessment of the effects on telephone connections of a d.a.g.c. that introduces gains of 6 dB or 12 dB. This work used a Telephone Connection Assessment Model developed at The University of Aston in Birmingham. The subjective tests showed that the d.a.g.c. gives advantage for listeners when the speech level is very low. The benefit is not great when speech is only a little quieter than preferred. The assessment showed that, when a standard British Telecom earphone is used, insertion of gain is desirable if speech voltage across the earphone terminals is below an upper limit of -38 dBV. People commented upon the presence of an adaptive-like effect during the tests. This could be the reason why they voted against the insertion of gain at level only little quieter than preferred, when they may otherwise have judged it to be desirable. A telephone connection with a d.a.g.c. in has a degree of difficulty less than half of that without it. The score Excellent plus Good is 10-30% greater.

Speaker verification based on the fusion of speech acoustics and inverted articulatory signals

We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.

Robust noise reduction for speech and audio signals

Statistical model-based methods are presented for the reconstruction of autocorrelated signals in impulsive plus continuous noise environments. Signals are modelled as autoregressive and noise sources as discrete and continuous mixtures of Gaussians, allowing for robustness in highly impulsive and non-Gaussian environments. Markov Chain Monte Carlo methods are used for reconstruction of the corrupted waveforms within a Bayesian probabilistic framework and results are presented for contaminated voice and audio signals.