Jyh-Da Wei and Hsin-Chen Tsai
Recognition by Online Modeling – a New Approach of Recognizing Voice Signals in Linear Time
535 - 538
2011
5
5
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/3663
https://publications.waset.org/vol/53
World Academy of Science, Engineering and Technology
This work presents a novel means of extracting fixedlength parameters from voice signals, such that words can be recognized
in linear time. The power and the zero crossing rate are first
calculated segment by segment from a voice signal; by doing so, two
feature sequences are generated. We then construct an FIR system
across these two sequences. The parameters of this FIR system, used
as the input of a multilayer proceptron recognizer, can be derived by
recursive LSE (leastsquare estimation), implying that the complexity of overall process is linear to the signal size. In the second part of
this work, we introduce a weighting factor λ to emphasize recent
input; therefore, we can further recognize continuous speech signals.
Experiments employ the voice signals of numbers, from zero to nine, spoken in Mandarin Chinese. The proposed method is verified to
recognize voice signals efficiently and accurately.
Open Science Index 53, 2011