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Speech is the primary means of human communication. Speech production starts in early ages and matures as children grow. People with intellectual or learning disabilities have deficit in speech production and faces difficulties in communication. These people need tailor-made therapies or trainings for rehabilitation to lead their lives independently. To provide these special trainings , it is important to know the exact nature of impairment in the speech through acoustic analysis. This study calculated the spectro-temporal features relevant to brain structures, encoded at short and long timescales in the speech of 82 subjects including 32 typically developing children, 20 adults and 30 participants with intellectual disabilities (severity ranges from mild to moderate). The results revealed that short timescales, which encoded information like formant transition in typically developing group were significantly different from intellectually disabled group, whereas long timescales were similar amongst groups. The short timescales were significantly different even within typically developing group but not within intellectually disabled group. The findings suggest that the features encoded at short timescales and ratio (short/long) play a significant role in classifying the group. It is shown that the classifier models with good accuracy can be constructed using acoustic features under investigation. This indicates that these features are relevant in differentiating normal and disordered speech. These classification models can help in early diagnostics of intellectual or learning disabilities.