Dual-channel speech enhancement based on stochastic optimization strategies

Asl, Laleh Badri; Geravanchizadeh, Masoud

doi:10.1109/isspa.2010.5605533

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…The Table 6. Highlights of optimization methods for enhancing speech Highlights LPSO [73] • Higher performance when compared to SPSO, GA, and gradient-based NLMS algorithm in terms of SNR improvement and stability. θ-PSO [74] • Combination of pros of both algorithms, θ-PSO and SSPSO • Quite effective in achieving global convergence for adaptive filters • Better suppression of noise in the input speech signal • Increased diversity of particles in the search space to avoid getting caught in local optima.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Techniques for Enhancing Speech

Tayseer¹,

Adeel²,

Hussain³

2018

IJCA

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Speech enhancement is used in almost all the modern communication systems. It is obvious that when speech is being transmitted, its quality may degrade due to interference in the environment it is passing through. Some of the interferences that may affect the speech quality of transit include acoustic additive noise, acoustic reverberation or white Gaussian noise. This paper focuses on the techniques that appeared in the literature to enhance the signal of speech. Various methods used include wiener filter, statistical methods, subspace method, basic spectral subtraction method and spectral subtraction. In this paper authors will discuss various such methods along with their advantages and disadvantages.

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Section: Discussionmentioning

confidence: 99%

“…In 2010, Learning-based Particle Swarm Optimization (LPSO), which is an improved stochastic optimization algorithm, was introduced to devise an adaptive filter for dual-channel speech enhancement application [73]. The search of region around the best solution is performed through dynamic search method.…”

Section: Learning-based Pso (Lpso)mentioning

confidence: 99%