ترکیب کردن گفتار مالایا قابلیت فهم بالای جای ضعف کامپیوتر براساس داده های آماری
LOW FOOTPRINT HIGH INTELLIGIBILITY MALAY SPEECH SYNTHESIZER BASED ON STATISTICAL DATA
نویسندگان |
این بخش تنها برای اعضا قابل مشاهده است ورودعضویت |
اطلاعات مجله |
thescipub.com |
سال انتشار |
2014 |
فرمت فایل |
PDF |
کد مقاله |
23360 |
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چکیده (انگلیسی):
Speech synthesis plays a pivotal role nowadays. It can be found in various daily applications such as in mobile
phones, navigation systems, languages learning software and so on. In this study, a Malay language speech
synthesizer was designed using hidden Markov model to improve the performance of current Malay speech
synthesizer and also extend Malay speech technology. Statistical parametric method was utilized in this study.
The database was constructed to be balanced with all the phonetic sample appeared in Malay language. The
results were rated by 48 listeners and obtained a moderate high rating ranging from 3.79 to 4.23 out of 5. The
computed Word Error Rate is 7.1%. The total file size is less than 2 Megabytes which means it is suitable to be
embedded into daily application. In conclusion, a Malay language speech synthesizer was designed using
statistical parametric method with hidden Markov model. The output speech was verified to be good in quality.
The file size is small indicates the feasibility to be used in embedded system.
کلمات کلیدی مقاله (فارسی):
نتيجه گيري ، مدل پنهان مارکوف ، آواشناسي متوازن ، جاي کامپيوتر
کلمات کلیدی مقاله (انگلیسی):
Keywords: Speech Synthesis, Hidden Markov Model, Phonetic Balanced, Footprint
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