Abstract
In this paper, we investigate the effect of temporal context for speech/ non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experimental evaluations on the test data set, with a state-of-the-art multi-layer perceptron based SND system and a simple energy threshold based SND method, using the F-measure, show an absolute performance gain of 4.4% and 5.4% respectively. The optimal contextual length was found to be 1000 ms. Further numerical optimizations yield an improvement (3.37% absolute), resulting in an absolute gain of 7.77% and 8.77% over the MLP based and energy based methods respectively. ROC based performance evaluation also reveals promising performance for the proposed method, particularly in low SNR conditions.
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Krishnan Parthasarathi, S.H., Motlíček, P., Hermansky, H. (2008). Exploiting Contextual Information for Speech/Non-Speech Detection. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_58
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DOI: https://doi.org/10.1007/978-3-540-87391-4_58
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