نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی پزشکی، گروه بیوالکتریک، دانشکده مهندسی‌ پزشکی، دانشگاه صنعتی امیرکبیر (پلی‌تکنیک ایران)

2 دانشیار، گروه بیوالکتریک، دانشکده مهندسی‌ پزشکی، دانشگاه صنعتی امیرکبیر (پلی‌تکنیک ایران)

10.22041/ijbme.2012.13096

چکیده

تحقیقات اخیر نشان می‌دهد که تظاهرات غیرخطی و آشوبی سیگنال گفتار می‌تواند در حوزة فضای بازسازی شده فاز (RPS) مطالعه شود. تئوری جاسازی برمبنای محورهای تأخیری، ابزار مناسبی برای بررسی تراژکتورهای گفتاری در RPS است. تاکنون از مشخصه‌های تراژکتورهای گفتاری به ندرت در سیستم‌های کاربردی بازشناسی گفتار استفاده شده است. از اینرو در این مقاله  روش استخراج ویژگی جدیدی براساس پارامترهای مدلسازی خطی مبتنی بر روش AR برداری (VAR) پیشنهاد شده است. در این روش بوسیله ماتریس ضرایب فیلتر و یا ضرایب انعکاسی به دست آمده از اعمال روش VAR بر مشخصه‌های استاتیک و دینامیک تراژکتوری های گفتاری شکل یافته در RPS، یک بردار ویژگی با بُعد زیاد حاصل می‌شود که می‌توان از روش‌های نگاشت خطی برای کاهش بُعد مناسب آن استفاده کرد. نتایج آزمایش‌های بازشناسی واج مجزا و پیوسته بر مجموعه دادگان گفتاری فارس‌دات نشان می‌دهد که کارایی این روش در مقایسه با دیگر روش‌های متداول استخراج ویژگی مبتنی بر حوزة زمان مانند روش LPC و LPREF بیشتر است. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Feature Extraction based on Linear Modeling of Embedded Speech Trajectory in the Reconstructed Phase Space for Speech Recognition System

نویسندگان [English]

  • Yaser Shekofteh 1
  • Farshad Almasganj 2

1 Ph.D Candidate, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

2 Associate Professor, Bioelectric Department, Faculty of Biomedical Engineering, Amirkabir University of Technology

چکیده [English]

Recent researches show that nonlinear and chaotic behavior of the speech signal can be studied in the reconstructed phase space (RPS). Delay embedding theorem is a useful tool to study embedded speech trajectories in the RPS. Characteristics of the speech trajectories have rarely used in the practical speech recognition systems. Therefore, in this paper, a new feature extraction (FE) method is proposed based on parameters of vector AR (VAR) analysis over the speech trajectories. In this method, using filter and reflection matrices obtained from applying VAR analysis on static and dynamic information of the speech trajectory in the RPS, a high-dimensional feature vector can be achieved. Then, different transformation methods are utilized to attain final feature vectors with appropriate dimension. Results of discrete and continuous phoneme recognition over FARSDAT speech corpus show that the efficiency of the proposed FE method is better than other time-domain-based FE methods such as LPC and LPREF.

کلیدواژه‌ها [English]

  • Speech Recognition
  • Feature Extraction
  • reconstructed phase space
  • Signal Embedding
  • Linear Prediction
  • Vector AR
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