|ترجمه عنوان مقاله||تشخیص و تصحیح گفتار لکنت زبان|
|عنوان انگلیسی مقاله||Speech Recognition and Correction of a Stuttered Speech|
|انتشار||مقاله سال ۲۰۲۲|
|تعداد صفحات مقاله انگلیسی||۴ صفحه|
|هزینه||دانلود مقاله انگلیسی رایگان میباشد.|
|پایگاه داده||نشریه IEEE|
|نوع نگارش مقاله
||مقاله پژوهشی (Research article)|
|مقاله بیس||این مقاله بیس میباشد|
|فرمت مقاله انگلیسی|
|رشته های مرتبط||پزشکی – مهندسی کامپیوتر|
|گرایش های مرتبط||روانپزشکی – هوش مصنوعی|
|نوع ارائه مقاله
||ژورنال – کنفرانسی|
|مجله / کنفرانس||کنفرانس بین المللی ۲۰۱۸ آی سی ای سی سی آی – ۲۰۱۸ International Conference ICACCI|
|دانشگاه||Department of Electronics and Communication Engineering, PES University, India|
|کلمات کلیدی||تشخیص گفتار – لکنت – شبکه های عصبی – سیستم تبدیل متن به گفتار|
|کلمات کلیدی انگلیسی||speech recognition – stutter – neural networks – TTS system|
|شناسه دیجیتال – doi
|وضعیت ترجمه مقاله||ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.|
|دانلود رایگان مقاله||دانلود رایگان مقاله انگلیسی|
|سفارش ترجمه این مقاله||سفارش ترجمه این مقاله|
|فهرست مطالب مقاله:|
II. LITERATURE REVIEW
III. PROPOSED DESIGN METHODOLOGY
IV. RESULTS AND DISCUSSIONS
|بخشی از متن مقاله:|
The aim of this paper is to develop an algorithm to enhance speech recognition of a stuttered speech. Stuttering is a disorder that affects the fluency of speech by involuntary repetition, prolongation of words/syllables, or involuntary silent intervals. Current speech recognition systems fail to recognize stuttered speech. Methods to detect stutter have been reported in literature but efficient techniques for stutter correction have not been reported. This paper addresses this issue and proposes methods to detect and correct stutter within acceptable time limits. To remove prolongation(s) from the sample, amplitude thresholding through neural networks is developed. Repetitions are removed through string repetition removal algorithm using an existing Text-to-Speech (TTS) system. Thus, the output signal, void of all stutters, produces better speech recognition.
Stuttering is a speech disorder characterized by repetition of sounds, syllables, or words; prolongation of sounds. An individual who faces this disorder knows what he or she intend to say but is unable to produce fluent speech. Millions of people, in today’s world, suffer from various speech disorders like stuttering, lisp, and articulation disorder. This often renders them unable to utilize certain things that a normal person takes for granted, like speech recognition systems.
Stuttering disorder is characterized by disruptions in the production of speech sounds, called disfluencies. Disfluencies are not necessarily a problem; however, they can hinder communication when a person produces too many of them. Most people often produce brief disfluencies. For instance, some words are repeated or prolonged while others are preceded by an ‘um’ or ‘uh’. In most cases, stuttering has an impact at least on some daily activities. The specific everyday activities that a person finds challenging to perform, vary across individuals. For example, for some people, communication difficulties happen only during specific activities, like talking on the phone, talking before large groups, utilizing everyday tools that use speech as inputs. An author claims, “Stuttering cannot be permanently cured; it may go into remission for a time, or clients can learn to shape their speech into fluent speech with the appropriate speech pathology treatment” .
The main objective of this paper is to present an algorithm that efficiently detects and corrects stutter in a speech segment of a person with stuttering speech disability. The proposed algorithm gives an accuracy level of 86% for 50 stutter speech samples. Two algorithms were used for more precise stutter removal system that can be built on any device.
The developed system can be incorporated into any existing speech recognition system. It can also serve as a speech therapy system where a user suffering from stutter can sound like the correct output obtained from the system. Hence the device can be used by people suffering from stutter to use the existing virtual assistant services, or talk to others with confidence using the device. This would enhance the level of communication amongst people with this disorder.