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The ongoing advancements in the multimedia technologies drive the need for efficient classification of the audio signals to make the content-based retrieval process more accurate and much easier from huge databases. The challenge of this task lies in an accurate extraction of signal characteristics so as to derive a strong discriminatory feature suitable for retrieval process. A time-frequency approach for audio classification is proposed. The audio signals were decomposed using an adaptive time-frequency decomposition algorithm, and the signal decomposition parameter octave (scale) was used to create patterns based on a similarity measure of the audio signals. These patterns were used to generate templates to classify the audio signals into different categories. Initial studies have yielded a overall correct classification accuracy of 90% with a database of 64 audio segments.