Recently, Quality of Experience (QoE) of voice service has been paid more attentions because it represents the performance of voice service subjectively perceived by the end users. And speech quality is commonly used to measure the QoE value. In this paper, a speech quality assessment algorithm is proposed for GSM network, aiming to predict and monitor QoE of voice service based on radio link parameters with low complexity for operators. Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) are combined and used to establish the mapping model from radio link parameters to speech quality. Data set for model training and testing is obtained from real commercial network of China Mobile. The experimental results show that with sufficient training data, this algorithm can predict radio speech quality with high accuracy and could be used to monitor speech quality of mobile network in real time.