Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   propose a new segmentation algorithm called delta MFCC based speech segmentation (DMFCC-SS), with application to speaker recognition systems.  show that DMFCC-SS can separate the regions of speech that result from similar likelihood scores using models such as a Gaussian mixture model (GMM), and can therefore be used to identify the regions of speech beten two transitional states in a speech signal. By combining this segmentation algorithm with the discriminative por of transient frames in speaker recognition,  can investigate the tradeoff in speed-up rates that result from DMFCC-SS, with speaker verification equal error rates that result from representatives of each segment.  use a universal background model Gaussian mixture model (UBM-GMM) as a baseline system. The proposed speed-up algorithm, working in the pre-processing stage, performs ll while having no computational load compared to the main GMM system. Experimental results show the superior performance of this pre-processing method in comparison with other algorithms working in the pre-processing stage of a UBM-GMM system.
['Rahim Saeidi', 'H. Mohammadi', 'Robert D. Rodman', 'Tomi Kinnunen']
I am writing a research paper on a idea A New Segmentation Algorithm Combined with Transient Frames Power for Text Independent Speaker Verification
[{"from": "human", "value": "I am writing a research paper on a idea A New Segmentation Algorithm Combined with Transient Frames Power for Text Independent 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:   propose a new segmentation algorithm called delta MFCC based speech segmentation (DMFCC-SS), with application to speaker recognition systems.  show that DMFCC-SS can separate the regions of speech that result from similar likelihood scores using models such as a Gaussian mixture model (GMM), and can therefore be used to identify the regions of speech beten two transitional states in a speech signal. By combining this segmentation algorithm with the discriminative por of transient frames in speaker recognition,  can investigate the tradeoff in speed-up rates that result from DMFCC-SS, with speaker verification equal error rates that result from representatives of each segment.  use a universal background model Gaussian mixture model (UBM-GMM) as a baseline system. The proposed speed-up algorithm, working in the pre-processing stage, performs ll while having no computational load compared to the main GMM system. Experimental results show the superior performance of this pre-processing method in comparison with other algorithms working in the pre-processing stage of a UBM-GMM system."}]