طراحی و جمع‌آوری دادگان گفتاری به‌عنوان گام نخست بومی‌سازی تشخیص هوشمند اوتیسم در کودکان ایرانی
محورهای موضوعی : مهندسی برق و کامپیوتر
مریم علیزاده
1
(پژوهشکده فضای مجازی، دانشگاه شهید بهشتی)
شیما طبیبیان
2
(پژوهشکده فضای مجازی، دانشگاه شهید بهشتی)
کلید واژه: تشخیص اوتیسم, پردازش گفتار, یادگیری ماشین, دادگان گفتاری, کودکان, زبان فارسی,
چکیده مقاله :
اختلال طیف اوتیسم، نوعی اختلال رشدی به شمار می‌آید که از طریق علائمی مانند ناتوانی در برقراری ارتباط اجتماعی، خود را نشان می‌دهد. بنابراین بارزترین نشانه افراد مبتلا به اوتیسم، اختلال گفتار است. این مقاله در بخش اول به بررسی و مرور مطالعات انجام‌شده برای تشخیص خودکار اوتیسم بر اساس پردازش گفتار افراد مشکوک به ابتلا می‌پردازد. با توجه به بررسی‌های انجام‌شده، رویکردهای اصلی پردازش گفتار برای تشخیص اوتیسم به دو گروه تقسیم می‌شوند. گروه اول با پردازش پاسخ‌ها یا احساسات افراد مورد آزمایش در پاسخ به سؤالات یا داستان پرسشگر، افراد مبتلا به اوتیسم را تشخیص می‌دهند. گروه دوم، افراد مبتلا به اوتیسم را از طریق میزان نرخ دقت بازشناسی گفتارشان در سیستم‌های تشخیص خودکار گفتار از افراد سالم تفکیک می‌کنند. علی‌رغم پژوهش‌های زیاد انجام‌شده در این حوزه در خارج از ایران، پژوهش‌های اندکی داخل ایران انجام شده‌اند که مهم‌ترین دلیل آن، عدم وجود دادگان غنی متناسب با نیازمندی‌های تشخیص اوتیسم مبتنی بر پردازش گفتار افراد مبتلا است. در بخش دوم پژوهش حاضر به روند طراحی، جمع‌آوری و ارزیابی یک مجموعه دادگان گفتاری مستقل از گوینده برای تشخیص اوتیسم در کودکان ایرانی به‌عنوان گام نخست بومی‌سازی حوزه مذکور پرداخته‌ایم.
Autism Spectrum Disorder is a type of disorder in which, the patients suffer from a developmental disorder that manifests itself by symptoms such as inability to social communication. Thus, the most apparent sign of autism is a speech disorder. The first part of this paper reviews research studies conducted to automatically diagnose autism based on speech processing methods. According to our review, the main speech processing approaches for diagnosing autism can be divided into two groups. The first group detects individuals with autism by processing their answers or feelings in response to questions or stories. The second group distinguishes people with autism from healthy people because of the accuracy of recognizing their spoken utterances based on automatic speech recognition systems. Despite much research being conducted outside Iran, few studies have been conducted in Iran. The most important reason for this is the lack of rich data that meet the needs of autism diagnosis based on the speech processing of suspected people. In the second part of the paper, we discuss the process of designing, collecting, and evaluating a speaker-independent dataset for autism diagnosis in Iranian children as the first step in the localization of the mentioned field.
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