تقطیع هجایی گفتار پیوسته فارسی با استفاده از آستانه‌گذاری ضرایب موجک و نرم‌سازی فازیِ تابع انرژی
محورهای موضوعی : انرژی های تجدیدپذیر
1 - کارشناس ارشد/شرکت جویشگر ریزگستر مستقر در شهرک علمی و تحقیقاتی اصفهان
2 - دانشکده برق، واحد نجف آباد، دانشگاه آزاد اسلامی
کلید واژه: واکه, همخوان, تبدیل موجک, تقطیع هجایی, آستانه‌گذاری ضرایب موجک, فیلتر فازی, انرژی زمان کوتاه,
چکیده مقاله :
امروزه در تحقیقات حوزه پردازش و بازشناخت گفتار، هجا به دلیل ارتباط قوی آن با تولید و ادراک گفتار در انسان، به عنوان یک واحد زیرکلمه‌ای هر روز بیشتر مورد توجه قرار می‌گیرد. آشکارسازی خودکار مرزهای هجایی گامی مهم در تحقیقات مرتبط با نوای گفتار، تولید گفتار طبیعی و حتی بازشناسی گفتار است. در این مقاله روش جدیدی برای آشکارسازی خودکار مرزهای هجایی در سیگنال گفتار پیوسته فارسی با تکیه بر اطلاعات صوتی ارائه شده است. تحقیقات قبلیِ نویسندگان این مقاله، کارآیی نرم‌سازی فازیِ تابع انرژی را در مقایسه با سایر روش‌های به کار رفته در این زمینه نشان می‌دهد. در این تحقیق، پیشنهاد شده است که از روشی مشابه روش‌های متداول حذف نویز از گفتار به وسیله آستانه گذاری ضرایب موجک برای بهبود خطای درج مرز اضافه استفاده شود. این روند، انرژی همخوان‌های بی‌واکی را که در تابع انرژی قله‌های اضافه ایجاد می‌کنند، به شدت کاهش می‌دهد. نتایج نشان می‌دهند با استفاده همزمان از این روش و روش نرم‌سازی فازی تابع انرژی، خطای درج مرز اضافه در حدود %8 کاهش می‌یابد؛ بدون آنکه سایر معیارهای کارآیی تحت تأثیر قرار گیرند. با استفاده از روش پیشنهادی بیش از %94 از هجاها با خطایی کمتر از 50 میلی‌ثانیه تقطیع می‌شوند.
Syllable, as a sub-word unit, nowadays plays an active role in the field of speech processing and recognition research according to its robust relation to human speech production and cognition. Automatic syllable boundaries detection is an important step forward in the areas of speech prosody, natural speech synthesis and speech recognition. In this paper, a novel method in automatic syllabification of Farsi continuous speech based on acoustic structure is proposed. Our previous studies, showed the proficiency of energy contour fuzzy smoothing method, compared with other prominent works in this area. This paper suggests that the conventional methodology-used in speech enhancement based on wavelet coefficient thresholding would improve syllable segmentation by decreasing insertion error. This process declines the energy in high energy consonants which are responsible for extra peaks in short term energy contour. Experimental results showed that utilizing proposed method along with fuzzy smoothing would diminish insertion error about 8% with no reasonable effect on other efficiency criteria. More than 94% of syllables are automatically segmented using presented technique with less than 50ms error.
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