With the growth in computing power, speech recognition carries a strong potential in the near future. It has even become increasingly popular with the development of mobile devices. Presumably, mobile devices have limited computational power, memory size and battery life. In general, speech recognition operation requires heavy computation due to large samples per window used. Fast Fourier Transfom (FFT) is the most popular transform to search for formant frequencies in speech recognition. In addition, FFT operates in complex fields with imaginary numbers. This paper proposes an approach based on Discrete Tchebichef Transform (DTT) as a possible alternative to FFT in searching for the formant frequencies. The experimental outputs in terms of the frequency formants using FFT and DTT have been compared. Interestingly, the experimental results show that both have produced relatively identical formant shape output in terms of basic vowels and consonants recognition. DTT has the same capability to recognize speech formants F 1 , F 2 , F 3 on real domains.