Transcription of Speech Recognition Using Deep Learning Algorithms
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Speech Recognition Using Deep Learning Algorithms
Speech Recognition Using Deep Learning Algorithms Yan Zhang, SUNet ID: yzhang5 Instructor: Andrew Ng Abstract: Automatic Speech Recognition , translating of spoken words into text, is still a challenging task due to the high viability in Speech signals. Deep Learning , sometimes referred as representation Learning or unsupervised feature Learning , is a new area of machine Learning . Deep Learning is becoming a mainstream technology for Speech Recognition and has successfully replaced Gaussian mixtures for Speech Recognition and feature coding at an increasingly larger scale. The main target of this course project is to applying typical deep Learning Algorithms , including deep neural networks (DNN) and deep belief networks (DBN), for automatic continuous Speech Recognition .
Speech Signal Decoder Recognized Words Acoustic Models Pronunciation Dictionary Language Models. Fig. 1 A typical system architecture for automatic speech recognition . 2. Automatic Speech Recognition System Model The principal components of a large vocabulary continuous speech reco[1] [2] are gnizer illustrated in Fig. 1.
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