Is AdaBoost competitive for phoneme classification?

In the phoneme classification task of speech recognition, usually Gaussian Mixture Models and Artificial Neural Networks are used. For other machine learning tasks, however, several other classification algorithms are also applied. One of them is AdaBoost.MH, reported to have high accuracy, which we tested for phoneme recognition on the well-known TIMIT dataset. We found that it can achieve an accuracy comparable to standard ANNs in this task, but lags behind recently-proposed Deep Neural Networks. Based on our experimental results, we list a number of possible reasons why this might be so.