Code-Mixed Street Address Recognition and Accent Adaptation for Voice-Activated Navigation Services

<p dir="ltr">This study presents the development of a real-time application-specific Automatic Speech Recognition (ASR) system for voice-activated navigation services. The system is designed to recognize Urdu-English code-mixed street addresses, which is challenging due to their comp...

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Bibliographic Details
Main Author:	Syed Meesam Raza Naqvi (22225462) (author)
Other Authors:	Muhammad Ali Tahir (6640979) (author), Kamran Javed (21726248) (author), Hassan Aqeel Khan (22225465) (author), Ali Raza (3558965) (author), Zubair Saeed (19325647) (author)
Published:	2024
Subjects:	Engineering Electronics, sensors and digital hardware Information and computing sciences Machine learning Urdu-English code-mixing roman Urdu addresses accent adaptation deep neural network Gaussian mixture models hidden Markov models voice-activated navigation Speech recognition Acoustics Vocabulary Speech coding Real-time systems Navigation Long short term memory Error analysis Switches Natural language processing
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Code-Mixed Street Address Recognition and Accent Adaptation for Voice-Activated Navigation Services

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