Isolated digit speech recognition in Malay language using Neuro-Fuzzy approach
Document Type
Conference Item
Publication Date
1-1-2009
Abstract
In this paper we discuss the development and implementation of an automated speaker-independent isolated Malay digit speech recognition system. The system is developed using Neuro-Fuzzy approach that combines the human-like reasoning style of fuzzy systems and the learning and connectionist structure of neural networks. To recognize the Malay speech digits, the endpoint detection algorithm is used to trim the silent duration in speech sample, the Mel Frequency Cepstral Coefficient technique is used to extract speech features, the subtractive clustering algorithm is applied to identify the fuzzy inference system, and the Adaptive Neuro Fuzzy Inference System (ANFIS) is used as a modern classification technique to train in identifying the features of speech. The performance of the system was evaluated by using 630 speech samples for training and testing, and experimental results showed that an overall 85.24% recognition rate was achieved.
Keywords
Isolated Word Speech Recognition System, Neuro-fuzzy, ANFIS
Divisions
fsktm
Event Title
3rd Asia International Conference on Modelling and Simulation
Event Location
Bundang, INDONESIA
Event Dates
MAY 25-29, 2009
Event Type
conference
Additional Information
Univ Malaya, Fac Comp Sci & Informat Technol, Kuala Lumpur, Malaysia