Fazal-e-Abbas Chaudhry MEE 07:33, pp. 121. TEK/avd. för telekommunikationssystem, 2007.
This report describes two important investigations which formed part of an overall project aimed at separating overlapping speech signals. The first investigation uses chirp signals to measure the acoustic transfer functions which would typically be found in the speaker separation project. It explains the behaviour of chirps in acoustic environments that can be further used to find the room reverberations as well, besides their relevance to measuring the transfer functions in conjunction with speaker separation. Chirps that have been used in this
part are logarithmic and linear chirps. They have different lengths and are analysed in two different acoustic environments. Major findings are obtained in comparative analysis of different chirps in terms of their cross-correlations, specgrams and power spectrum magnitude.
The second investigation deals with using automatic speech recognition (ASR) system to test the performance of the speaker separation algorithm with respect to word accuracy of different speakers. Speakers were speaking in two different scenarios and these were nonoverlapping
and overlapping scenarios. In non-overlapping scenario speakers were speaking alone and in overlapping scenario two speakers were speaking simultaneously.
To improve the performance of speaker separation in the overlapping scenario, I was working very close with my fellow colleague Mr. Holfeld who was improving the existing speech separation algorithm. After cross-examining our findings, we improved the existing speech separation algorithm. This further led to improvement in word accuracy of the speech recognition software in overlapping scenario.
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