Noisy speech endpoint detection based on approximate entropy
Ling Li · Shengxue jishu · 2007
To improve performance of endpoint detection in noisy environment is an important issue in automatic speech recognition(ASR),especially in actual noisy environments.The performance of conventional endpoint detection methods based on short-time energy and zero-crossing rate is unsatisfactory in environments of low SNR.Approximate entropy is a new statistical method of complexity measurement in measuring time series complexity.It is quite stable with changing data length and has strong anti-interference ability.In this paper,a method of noisy speech endpoint detection based on approximate entropy(ApEn)is proposed.Simulation results indicate that the method has good performance even in low SNR circumstances.