Modulation scheme is one of the most important characteristics to note in the monitoring activity and identification of radio signals. Modulation recognition system must be able to make the correct classification of the modulation scheme of the received signal under interference. AMR is required in both military and civilian applications, such as surveillance, electronic warfare, threat assessment, signal confirmation, interference identification, software defined radio, and spectrum management. AMR is also believed to play an important role in the implementation of the 4th-Generation (4G) communication system. A generalized modulation identification scheme is developed and presented. With the help of this scheme, the automatic modulation classification and recognition of digitally modulated speech signals with a priori unknown parameters are possible effectively. The developed scheme based on wavelet transform and statistical parameters has been used to identify M-ary PSK, M-ary QAM, and M-ary FSK modulations. Various speech signals corrupted by noise have been used as sample signals .Statistical parameters are calculated and compared against certain threshold values to detect the modulation type. The simulated results show that the correct modulation identification is possible to a lower bound of 15 dB.