Adaptive Compensation Algorithm in Open Vocabulary Mandarin Speaker-Independent Speech Recognition

IntroductionA speech signal is normally mixed with many kindsof noises,which can significantly decrease theperformance of a speech recognizer.The highconcentration of energy in the low frequency rangeobserved for most speech spectra is considered anuisance because it makes less relevant the energyof the signal at middle and high frequencies1] .　The performance of automatic continuous speechrecognition (ACSR ) systems dramaticallydecreases when they are trained and used indifferent environm…

Adaptive Compensation Algorithm in Open Vocabulary Mandarin Speaker-Independent Speech Recognition

In speech recognition systems, the physiological characteristics of the speech production model cause the voiced sections of the speech signal to have an attenuation of approximately 20 dB per decade. Many speech recognition algorithms have been developed to solve this problem by filtering the input signal with a single-zero high pass filter. Unfortunately, this technique increases the noise energy at high frequencies above 4 kHz, which in some cases degrades the recognition accuracy. This paper solves the problem using a pre-emphasis filter in the front end of the recognizer. The aim is to develop a modified parameterization approach taking into account the whole energy zone in the spectrum to improve the performance of the existing baseline recognition system in the acoustic phase. The results show that a large vocabulary speaker-independent continuous speech recognition system using this approach has a greatly improved recognition rate.