Name
Title | ||
|---|---|---|
Incorporating pass-phrase dependent background models for text-dependent speaker verification. |
Abstract | ||
|---|---|---|
•Propose pass-phrase dependent background model (PBM) for in text-dependent speaker verification (SV).•Consider two approaches to build PBMs: speaker independent and dependent.•PBM significantly reduces the error rates of TD-SV for target- and impostor-wrong.•Performance is demonstrated on GMM-UBM, HMM-UBM and i-vector paradigms.•Conduct experiments on the RedDots and RSR2015 databases consisting of short utterances.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.csl.2017.07.010 | Computer Speech & Language |
Keywords | Field | DocType |
Pass-phrase dependent background models (PBMs),GMM-UBM,HMM-UBM,I-vector,Text-dependent,Speaker verification | Speaker verification,Training set,Likelihood-ratio test,Pattern recognition,Computer science,Maximum likelihood,Phrase,Utterance,Speech recognition,Artificial intelligence,Hidden Markov model,Mixture model | Journal |
Volume | Issue | ISSN |
47 | C | 0885-2308 |
Citations | PageRank | References |
2 | 0.39 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Achintya Kumar Sarkar | 1 | 23 | 7.81 |
| Zheng-Hua Tan | 2 | 457 | 60.32 |