Analysis of Acoustic Feature Extraction Algorithms in Noisy Environments
نویسندگان
چکیده
Acoustic feature extraction algorithms play a central role in many speech and music processing applications. However, noise usually prevents acoustic feature extraction algorithms from obtaining the correct information from speech and music signals. Thus, the robustness of acoustic feature extraction algorithms is an area worth studying. In this thesis, we consider two important acoustic features: pitch and speaking rate. For each acoustic feature, we introduce several classic and state-of-the-art feature extraction algorithms and evaluate the performance of each of them in noisy environments. We analyze the results and provide possible explanations why some feature extraction algorithms outperform the others in noisy environments.
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