بهبود سرعت و دقت در استفاده از برنامه‌نويسي ژنتيک براي تصديق هويت گوينده
الموضوعات :
سعيده سادات سديدپور
1
(دانشگاه صنعتي اميرکبير)
محمدمهدی همایون‌پور
2
(دانشگاه صنعتی امیرکبیر)
مهدي فسنقري
3
(پژوهشکده فناوري اطلاعات)
الکلمات المفتاحية: گوينده تصديق هويت گوينده برنامه‌نويسي ژنتيک خوشه‌بندي ويژگی MFCC ويژگی PLP,
ملخص المقالة :
در تصديق هويت گوينده، سيستم هويت شخصي را که با سيستم تماس برقرار کرده است، بررسي کرده و تعيين مي‌کند که وي همان شخص مدعي است و يا دروغ مي‌گويد. در اين مقاله از برنامه‌نويسي ژنتيک به‌عنوان روشی برای مدل‌سازي گويندگان استفاده شد. با توجه به زمان زياد آموزش مدل‌ها توسط برنامه‌نويسي ژنتيک، ايده بهره‌مندي از فشرده‌سازي داده‌هاي آموزشي، بهمنظور کاهش زمان آموزش مدل‌ها مطرح گرديد و بدين ترتيب زمان لازم برای مدل‌سازی گويندگان با استفاده از برنامه‌نويسي ژنتيک در حدود 20 برابر کاهش داده شد. آموزش چندين درخت برنامه‌نويسي ژنتيک به‌عنوان مدل هر گوينده، ايده ديگري است که بهمنظور بهبود دقت تصديق هويت گوينده در اين مقاله مطرح شده است. در اين روش، داده‌هاي آموزشي به تعداد کمي خوشه تفکيک شده و به‌ازاي هر خوشه، يک درخت برنامه‌نويسي ژنتيک آموزش داده مي‌شود. بدين ترتيب يک گوينده با چندين درخت برنامه‌نويسي ژنتيک مدل مي‌شود. با استفاده از روش پيشنهادي، کارايي برنامه‌نويسي ژنتيک براي تصديق هويت گوينده از 50% به حدود 92% افزايش پيدا کرده است. نتايج حاصل از عملکرد برنامه‌نويسي ژنتيک با کارايي روش‌هاي تمايزي ديگري مثل شبکه‌های عصبي MLP و LVQ و نيز روش‌هاي غير تمايزي مانند LBG، GMM، GMM-UBM و VQ-MAP مقايسه گرديد و مشاهده شد که برنامه‌نويسي ژنتيک کارايي بهتري را نسبت به ديگر روش‌ها نتيجه مي‌دهد.
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