Speech is one of the most important skills in human normal life. It is the result of the coordinated movement of the articulation-related muscles under the control of central cervous system. Surface electromyography (sEMG) is a commonly used method for collecting electrical signals of muscles, which can detect reliable electrophysiological information. When using electromyographic signals on speech classification, the selected electrode position plays an important role in classification accuracy. However, the current sEMG-based speech recognition method does not have an objective index for selecting the position and number of electrodes, and it is still unclear whether the contribution of the articulation related symmetrical position electrodes on the left and right sides of the face and neck to speech recognition is redundant. In this study, the facial and neck sEMG of 8 subjects with normal pronunciation were collected by using a 120-channel electrode (about facial and neck symmetry) when they pronounced 5 Chinese words and 5 English words respectively. The contribution of sEMG in the symmetrical position of left and right sides of facial and neck to speech recognition was investigated. The results show that the muscles of the left and right sides of the face and neck had similar variation, but the correlation between the symmetrical positions of the face and neck was lower than that of the neck. There was little difference in classification accuracy between the left and right sEMG signals of the neck, but significant difference between the left and right SEMG signals of the face. Thus, sEMG signals from symmetrical positions in the neck are consistent in their contribution to speech recognition, whereas facial signals are not, which might provide useful clue to reduce the electrode number and select the optimal location of channels for speech recognition.