C. Santhosh Kumar

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BACKGROUND Susceptibility to lung cancer has been shown to be modulated by inheritance of polymorphic genes encoding cytochrome P450 1A1 (CYP1A1) and glutathione S transferases (GSTM1 and GSTT1), which are involved in the bioactivation and detoxification of environmental toxins. This might be a factor in the variation in lung cancer incidence with(More)
In this paper, we present a unified approach for hidden markov model based multilingual speech recognition. The proposed approach could be used across acoustically similar as well as diverse languages. We use an automatic phone mapping algorithm to map phones across languages and reduce the effective number of phones in the multililingual acoustic model. We(More)
We use similarities with people we know already as a means to enhance the speaker verification accuracy. Motivated by this, we use cosine distance similarities with a set of reference speakers, cosine distance features (CDF), to improve the performance of speaker verification systems for clean and additive noise test conditions. We used mel frequency(More)
This paper presents the design specifications of an experimental setup capable of injecting faults in a synchronous generator to develop and test algorithms for condition based maintenance of aerospace applications. A 3 kVA alternator is designed to inject faults in the stator winding and field windings. The system is capable of injecting open and short(More)
Speaker verification (SV) systems need to be robust to mimicked voices of target speakers as non-target trials to make them usable in critical applications. However, the performance of SV systems for mimicked voice test conditions has not been extensively explored. In an earlier work, we used Amrita SRE database to evaluate the performance of different(More)
This paper studies the contribution of different phones in speech data towards improving the performance of text/language independent speaker recognition systems. This work is motivated by the fact that the removal of silence segments from the speech data improves the system performance significantly as it does not contain any speaker-specific information.(More)