IMPACT OF MICROPHONE POSITIONAL ERRORS ON SPEECH INTELLIGIBILITY

The speech of a person speaking in a noisy environment can be enhanced through electronic beamforming using spatially distributed microphones. As this approach demands precise information about the microphone locations, its application is limited in places where microphones must be placed quickly or changed on a regular basis. Highly precise calibration or measurement process can be tedious and time consuming. In order to understand tolerable limits on the calibration process, the impact of microphone position error on the intelligibility is examined. Analytical expressions are derived by modeling the microphone position errors as a zero mean uniform distribution. Experiments and simulations were performed to show relationships between precision of the microphone location measurement and loss in intelligibility. A variety of microphone array configurations and distracting sources (other interfering speech and white noise) are considered. For speech near the threshold of intelligibility, the results show that microphone position errors with standard deviations less than 1.5cm can limit losses in intelligibility to within 10% of the maximum (perfect microphone placement) for all the microphone distributions examined. Of different array distributions experimented, the linear array tends to be more vulnerable whereas the non-uniform 3D array showed a robust performance to positional errors

A robust sequential hypothesis testing method for brake squeal localisation

This contribution deals with the in situ detection and localisation of brake squeal in an automobile. As brake squeal is emitted from regions known a priori, i.e., near the wheels, the localisation is treated as a hypothesis testing problem. Distributed microphone arrays, situated under the automobile, are used to capture the directional properties of the sound field generated by a squealing brake. The spatial characteristics of the sampled sound field is then used to formulate the hypothesis tests. However, in contrast to standard hypothesis testing approaches of this kind, the propagation environment is complex and time-varying. Coupled with inaccuracies in the knowledge of the sensor and source positions as well as sensor gain mismatches, modelling the sound field is difficult and standard approaches fail in this case. A previously proposed approach implicitly tried to account for such incomplete system knowledge and was based on ad hoc likelihood formulations. The current paper builds upon this approach and proposes a second approach, based on more solid theoretical foundations, that can systematically account for the model uncertainties. Results from tests in a real setting show that the proposed approach is more consistent than the prior state-of-the-art. In both approaches, the tasks of detection and localisation are decoupled for complexity reasons. The localisation (hypothesis testing) is subject to a prior detection of brake squeal and identification of the squeal frequencies. The approaches used for the detection and identification of squeal frequencies are also presented. The paper, further, briefly addresses some practical issues related to array design and placement. (C) 2019 Author(s)

Mathematical modelling ano optimization strategies for acoustic source localization in reverberant environments

La presente Tesis se centra en el uso de técnicas modernas de optimización y de procesamiento de audio para la localización precisa y robusta de personas dentro de un entorno reverberante dotado con agrupaciones (arrays) de micrófonos. En esta tesis se han estudiado diversos aspectos de la localización sonora, incluyendo el modelado, la algoritmia, así como el calibrado previo que permite usar los algoritmos de localización incluso cuando la geometría de los sensores (micrófonos) es desconocida a priori. Las técnicas existentes hasta ahora requerían de un número elevado de micrófonos para obtener una alta precisión en la localización. Sin embargo, durante esta tesis se ha desarrollado un nuevo método que permite una mejora de más del 30\% en la precisión de la localización con un número reducido de micrófonos. La reducción en el número de micrófonos es importante ya que se traduce directamente en una disminución drástica del coste y en un aumento de la versatilidad del sistema final. Adicionalmente, se ha realizado un estudio exhaustivo de los fenómenos que afectan al sistema de adquisición y procesado de la señal, con el objetivo de mejorar el modelo propuesto anteriormente. Dicho estudio profundiza en el conocimiento y modelado del filtrado PHAT (ampliamente utilizado en localización acústica) y de los aspectos que lo hacen especialmente adecuado para localización. Fruto del anterior estudio, y en colaboración con investigadores del instituto IDIAP (Suiza), se ha desarrollado un sistema de auto-calibración de las posiciones de los micrófonos a partir del ruido difuso presente en una sala en silencio. Esta aportación relacionada con los métodos previos basados en la coherencia. Sin embargo es capaz de reducir el ruido atendiendo a parámetros físicos previamente conocidos (distancia máxima entre los micrófonos). Gracias a ello se consigue una mejor precisión utilizando un menor tiempo de cómputo. El conocimiento de los efectos del filtro PHAT ha permitido crear un nuevo modelo que permite la representación 'sparse' del típico escenario de localización. Este tipo de representación se ha demostrado ser muy conveniente para localización, permitiendo un enfoque sencillo del caso en el que existen múltiples fuentes simultáneas. La última aportación de esta tesis, es el de la caracterización de las Matrices TDOA (Time difference of arrival -Diferencia de tiempos de llegada, en castellano-). Este tipo de matrices son especialmente útiles en audio pero no están limitadas a él. Además, este estudio transciende a la localización con sonido ya que propone métodos de reducción de ruido de las medias TDOA basados en una representación matricial 'low-rank', siendo útil, además de en localización, en técnicas tales como el beamforming o el autocalibrado

A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) Determined from Phased Microphone Arrays

Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics

Implementation and evaluation of a low complexity microphone array for speaker recognition

Includes bibliographical references (leaves 83-86).This thesis discusses the application of a microphone array employing a noise canceling beamforming technique for improving the robustness of speaker recognition systems in a diffuse noise field

Deconvolution methods and systems for the mapping of acoustic sources from phased microphone arrays

A method and system for mapping acoustic sources determined from a phased microphone array. A plurality of microphones are arranged in an optimized grid pattern including a plurality of grid locations thereof. A linear configuration of N equations and N unknowns can be formed by accounting for a reciprocal influence of one or more beamforming characteristics thereof at varying grid locations among the plurality of grid locations. A full-rank equation derived from the linear configuration of N equations and N unknowns can then be iteratively determined. A full-rank can be attained by the solution requirement of the positivity constraint equivalent to the physical assumption of statically independent noise sources at each N location. An optimized noise source distribution is then generated over an identified aeroacoustic source region associated with the phased microphone array in order to compile an output presentation thereof, thereby removing the beamforming characteristics from the resulting output presentation

A Geometric Approach to Sound Source Localization from Time-Delay Estimates

This paper addresses the problem of sound-source localization from time-delay estimates using arbitrarily-shaped non-coplanar microphone arrays. A novel geometric formulation is proposed, together with a thorough algebraic analysis and a global optimization solver. The proposed model is thoroughly described and evaluated. The geometric analysis, stemming from the direct acoustic propagation model, leads to necessary and sufficient conditions for a set of time delays to correspond to a unique position in the source space. Such sets of time delays are referred to as feasible sets. We formally prove that every feasible set corresponds to exactly one position in the source space, whose value can be recovered using a closed-form localization mapping. Therefore we seek for the optimal feasible set of time delays given, as input, the received microphone signals. This time delay estimation problem is naturally cast into a programming task, constrained by the feasibility conditions derived from the geometric analysis. A global branch-and-bound optimization technique is proposed to solve the problem at hand, hence estimating the best set of feasible time delays and, subsequently, localizing the sound source. Extensive experiments with both simulated and real data are reported; we compare our methodology to four state-of-the-art techniques. This comparison clearly shows that the proposed method combined with the branch-and-bound algorithm outperforms existing methods. These in-depth geometric understanding, practical algorithms, and encouraging results, open several opportunities for future work.Comment: 13 pages, 2 figures, 3 table, journa