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Cognitive decline, a hallmark of several neurological conditions, including dementia and Alzheimer's disease, often manifests in noticeable changes in speech patterns and language use. Speech analysis in this context can serve as a valuable tool for early detection and monitoring of cognitive impairment. In this paper, we present the results of our attempts at the TAUKADIAL Challenge for automatically detecting people with mild cognitive impairment and predicting a cognitive score on English and Chinese speakers. In the classification task, we achieved a UAR of 83% using two language-dependent classifiers trained with timing and acoustic features. In the regression task, we obtained an RMSE of 1.87 using English speakers to train the base model with timing, acoustic, and language-dependent features.