Isolated Word Recognition Using by Patil Mahesh (5 results)

Paperback. Condition: Brand New. 80 pages. 8.66x5.91x0.19 inches. In Stock.

Taschenbuch. Condition: Neu. Neuware -Speech recognition has been an integral part of human life acting as one of the five senses of human body, because of which application developed on the basis of speech recognition has high degree of acceptance. The analysis of the different steps involved in isolated word recognition using Mel Frequency cepstral coefficients (MFCC), Vector quantization (VQ) and Hidden Markov Model (HMM) is seen here. The simple and efficient approach is used here which can be utilised in embedded systems. After analysing the steps above we realised the process using small programs using MATLAB which is able to do small number of isolated word recognition.The work done here develops a speaker independent isolated word recognizer from the acoustic signals based on a discrete observation Hidden Markov Model (HMM). The study implements the HMM based isolated word recognizer in three steps- Speech Segmentation,Feature extraction and Feature Matching.Books on Demand GmbH, Überseering 33, 22297 Hamburg 80 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Speech recognition has been an integral part of human life acting as one of the five senses of human body, because of which application developed on the basis of speech recognition has high degree of acceptance. The analysis of the different steps involved in isolated word recognition using Mel Frequency cepstral coefficients (MFCC), Vector quantization (VQ) and Hidden Markov Model (HMM) is seen here. The simple and efficient approach is used here which can be utilised in embedded systems. After analysing the steps above we realised the process using small programs using MATLAB which is able to do small number of isolated word recognition.The work done here develops a speaker independent isolated word recognizer from the acoustic signals based on a discrete observation Hidden Markov Model (HMM). The study implements the HMM based isolated word recognizer in three steps- Speech Segmentation,Feature extraction and Feature Matching. 80 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Speech recognition has been an integral part of human life acting as one of the five senses of human body, because of which application developed on the basis of speech recognition has high degree of acceptance. The analysis of the different steps involved in isolated word recognition using Mel Frequency cepstral coefficients (MFCC), Vector quantization (VQ) and Hidden Markov Model (HMM) is seen here. The simple and efficient approach is used here which can be utilised in embedded systems. After analysing the steps above we realised the process using small programs using MATLAB which is able to do small number of isolated word recognition.The work done here develops a speaker independent isolated word recognizer from the acoustic signals based on a discrete observation Hidden Markov Model (HMM). The study implements the HMM based isolated word recognizer in three steps- Speech Segmentation,Feature extraction and Feature Matching.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Patil MaheshProf. Mahesh K. Patil completed M.E.(Electronics Engg.) from Shivaji University India. He is currently working as Assistant Professor in DKTES s TEI Ichalkarnji,Maharashtra, India. His academic experience is 6 years. His .