A sparse reconstruction method for speech source localization using partial dictionaries over a spherical microphone array

نویسندگان

  • Kushagra Singhal
  • Rajesh M. Hegde
چکیده

Sparse reconstruction methods have been used extensively for source localization over uniform linear arrays and circular arrays. In this paper a sparse reconstruction method for speech source localization using partial dictionaries over a spherical microphone array is proposed. The source localization method proposed in this work addresses two important research issues. It formulates the source localization problem in the spherical harmonics domain as a sparse reconstruction problem. Subsequently, a low complexity method to estimate the direction of arrival (DOA) of multiple sources is also proposed by using partial elevation angle dictionaries. The use of such dictionaries reduces the complexity of the search involved in the two dimensional DOA estimation. Source localization experiments are conducted at different SNRs and compared with conventional DOA estimation methods like MUSIC and MVDR. The experimental results obtained from the proposed method indicate a reasonable reduction in the localization error.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Joint source localization and separation in spherical harmonic domain using a sparsity based method

In this paper, we address the problem of source localization and separation using sparse methods over a spherical microphone array. A sparsity based method is developed from the observed data in spherical harmonic domain. A solution to the sparse model formulated herein is obtained by imposing orthonormal constraint on the sparsity matrix. Subsequently, a splitting method based on bregman itera...

متن کامل

Sound Source Localization Using Non-Conformal Surface Sound Field Transformation Based on Spherical Harmonic Wave Decomposition

Spherical microphone arrays have been paid increasing attention for their ability to locate a sound source with arbitrary incident angle in three-dimensional space. Low-frequency sound sources are usually located by using spherical near-field acoustic holography. The reconstruction surface and holography surface are conformal surfaces in the conventional sound field transformation based on gene...

متن کامل

A New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain

Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...

متن کامل

Computational methods for underdetermined convolutive speech localization and separation via model-based sparse component analysis

In this paper, the problem of speech source localization and separation from recordings of convolutive underdetermined mixtures is studied. The problem is cast as recovering the spatio-spectral speech information embedded in a microphone array compressed measurements of the acoustic field. A model-based sparse component analysis framework is formulated for sparse reconstruction of the speech sp...

متن کامل

Voice-based Age and Gender Recognition using Training Generative Sparse Model

Abstract: Gender recognition and age detection are important problems in telephone speech processing to investigate the identity of an individual using voice characteristics. In this paper a new gender and age recognition system is introduced based on generative incoherent models learned using sparse non-negative matrix factorization and atom correction post-processing method. Similar to genera...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014