Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Usually the mel-frequency cepstral coefficients are estimated either from a periodogram or from a windod periodogram.  state a general estimator which also includes multitaper estimators.  propose approximations of the variance and bias of the estimate of each coefficient. By using Monte Carlo computations,  demonstrate that the approximations are accurate. Using the proposed formulas, the peak matched multitaper estimator is shown to have low mean square error (squared bias + variance) on speech-like processes. It is also shown to perform slightly better in the NIST 2006 speaker verification task as compared to the Hamming window conventionally used in this context.
['Johan Sandberg', 'Maria Hansson-Sandsten', 'Tomi Kinnunen', 'Rahim Saeidi', 'Patrick Flandrin', 'Pierre Borgnat']
I am writing a research paper on a idea Multitaper Estimation of Frequency-Warped Cepstra With Application to Speaker Verification
[{"from": "human", "value": "I am writing a research paper on a idea Multitaper Estimation of Frequency-Warped Cepstra With Application to Speaker Verification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Usually the mel-frequency cepstral coefficients are estimated either from a periodogram or from a windod periodogram.  state a general estimator which also includes multitaper estimators.  propose approximations of the variance and bias of the estimate of each coefficient. By using Monte Carlo computations,  demonstrate that the approximations are accurate. Using the proposed formulas, the peak matched multitaper estimator is shown to have low mean square error (squared bias + variance) on speech-like processes. It is also shown to perform slightly better in the NIST 2006 speaker verification task as compared to the Hamming window conventionally used in this context."}]