Abstract
Formants can reflect the resonance feature of the vocal tract, which form the spectral components of speech signal, and are closely related to speech intelligibility. Reverberation has an influence on formants, and Reverberation Time (RT) and Direct-to-Reverberant energy Ratio (DRR) are the primary parameters for reverberation strength judgement. Given some selected RT, cluster reverberant speech signals at different DRR by formants in order to achieve the purpose of recognizing reverberation level. Train formants of the reverberant speech signals using Gaussian Mixture Model (GMM), and verify the efficiency via 10-fold cross validation, and choose frequently used MFCC as comparison. Experiments prove formants can be used as an index for reverberation level recognition with satisfactory efficiency.
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The authors thank Prof. W.-Y. Chan and Prof. S.-Y. Yu for their guidances for this research.
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Ma, S., Li, H., Zhang, H., Xie, X. (2018). Reverberation Level Recognition by Formants Based on 10-Fold Cross Validation of GMM. In: Zhai, G., Zhou, J., Yang, X. (eds) Digital TV and Wireless Multimedia Communication. IFTC 2017. Communications in Computer and Information Science, vol 815. Springer, Singapore. https://doi.org/10.1007/978-981-10-8108-8_15
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