بهبود کیفیت گفتار مبتنی بر بهینه‌سازی ازدحام ذرات با استفاده از ویژگی های ماسک گذاری سیستم شنوائی انسان

نویسندگان

دانشگاه تبریز

چکیده

چکیده: در این مقاله، روش‌های دوکاناله جدید زیرفضایی سیگنال با استفاده از تکنیک‌های حذف نویز ادراکی برای بهبود کیفیت سیگنال گفتار پیشنهاد شده‌اند. روش‌های پیشنهادی از مشخصات ماسک‌گذاری سیستم شنوایی انسان برای کاهش نویز باقی­مانده قابل­شنیدن بهره می‌گیرند. روش تجزیه به مقادیر منفرد کسری ادراکی، تکنیک بهینه‌سازی ذرات را برای تخمین نویز جمعی استفاده می‌کند. نتایج شبیه‌سازی دقیقی که توسط دو معیار مختلفsubjectiveوobjectiveارزیابی شده است، نشان‌دهنده کیفیت بهتر سیگنال پردازش­شده توسط روش‌های پیشنهادی نسبت به الگوریتم‌های قبلی با هر دو نوع نویز ایستا و غیر‌ایستا و به‌خصوص نویز غیر‌سفید است.

کلیدواژه‌ها

عنوان مقاله [English]

PSO-Based Speech Enhancement using Masking Properties of Human Auditory system

چکیده [English]

Abstract: New dual-channel perceptually motivated subspace-based approaches are proposed for enhancement of speech corrupted by noise. The proposed methods take the frequency masking properties of the human auditory system into account and reduce perceptual effects of the residual noise. The perceptually constrained quotient singular value decomposition (PCQSVD) algorithm uses the particle swarm optimization (PSO) technique to estimate the additive noise. Very carefully performed objective evaluations and subjective tests show that the proposed approaches here can offer improved speech quality, as compared to previous methods, in the case of stationary and nonstationary noises, especially when the additive noise is nonwhite.

کلیدواژه‌ها [English]

  • Keywords: Auditory masking threshold
  • least-squares estimation
  • minimum-variance estimation
  • particle swarm optimization
  • quotient singular value decomposition
  • speech enhancement

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