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Enhancing Speaker Recognition System: Research Updates from Seungchan Lee

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Discover the latest research updates from Seungchan Lee at the Institute for Signal and Information Processing. Explore experiments with HMM using MFCCs and invariants, resolving isip_verify issues, and plans for future research topics in speaker recognition.

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Enhancing Speaker Recognition System: Research Updates from Seungchan Lee

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  1. Research Updates Seungchan Lee Institute for Signal and Information Processing Department of Electrical and Computer Engineering

  2. Overview • Speaker Recognition System • Replicate Tang’s experiment • Resolve new isip_verify problem • Do Experiment with HMM using the MFCCs and invariants • Tried to tune the parameters in Lyapunov exponent • Modify isip_run • Data Transfer to ECE • Next Plans

  3. Resolve isip_verify problem • It does not load StatisticalModel into Search engine in VerifyHMM class. • The result hypothesis scores is highly less than previous result • The “ACCEPTED” and “REJECTED” hypothesis does not give correct decision. New system Old system ACCEPTED: 1.70586e-05 (KAAA) REJECTED: -0.000698179 (KAAB) ACCEPTED: 2.19704e-05 (KAAC) REJECTED: -0.00218273 (KAAD) REJECTED: -0.000529905 (KAAG) REJECTED: -0.842606 (KAAA) REJECTED: -2.53688 (KAAB) REJECTED: -0.827423 (KAAC) REJECTED: -0.803932 (KAAD) REJECTED: -1.15936 (KAAG) All problems were resolved after fixing VerifyHMM class

  4. Speaker Recognition using invariants • Started from Lyapunov exponent • Remove delta coefficientsfrom MFCC  13 dim • Add Lyapunov exponent  14 dim • The result is worse than MFCC only.  We need to find different modeling method

  5. Speaker Recognition using invariants • Started from Lyapunov exponent • Remove delta coefficient from MFCC  13 dim • Add Lyapunov exponent  14 dim • The result is worse than MFCC only.  We need to find different modeling method

  6. Cluster at ECE • New isip_run design • Cluster management software is different between at CAVS and at ECE. • It requires different job command and script file at ECE. • Add generateScript() and generateCommand() in Splitter class. • It can afford to add several clusters at the different location.

  7. Data transfer to ECE • I’m ready for transferring data, but we have some problems. • Transfer speed ( 6 hours for 4.9G) • Is that possible to transfer several directories at a time. • Read only mode - Disk at ECE • PC availability  run a job in the background • File Permission at CAVS • After finishing transfer, we need to verify the data. • Data size • Continuously reduced and will reduce the size. • Verification of the data • The size and the number of files • Selectively choose several files, and compare them corpora corpora 115G 146G 648G exp 476G exp 201G 216G 160G research research 286G

  8. Next Plan • Speaker Recognition Experiment • Do Experiment with HMM using the MFCCs and invariants • Find new modeling methods for invariants • Thesis • Select the research topics - Speaker recognition using prosodic features - Speaker recognition using nonlinear invariants

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