Speaker recognition: a tutorial
J.P. Campbell low
A tutorial on the design and development of automatic speaker-recognition systems is presented. Automatic speaker recognition is the use of a machine to recognize a person from a spoken phrase. These systems can operate in two modes: to identify a particular person or to verify a person's claimed identity. Speech processing and the basic components of automatic speaker-recognition systems are shown and design tradeoffs are discussed. Then, a new automatic speaker-recognition system is given. This recognizer performs with 98.9% correct decalcification. Last, the performances of various systems are compared.
Citation edge evidence
- Distributed Systems: Principles and Paradigms→Speaker recognition: a tutorialLegacy edge — source detail unavailable
- An overview of text-independent speaker recognition: From features to supervectors→Speaker recognition: a tutorialLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→A tutorial on hidden Markov models and selected applications in speech recognitionLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→Introduction to Statistical Pattern RecognitionLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→Fundamentals of speech recognitionLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→Information theory and statisticsLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→An introduction to hidden Markov modelsLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→Pattern Recognition PrinciplesLegacy edge — source detail unavailable
- Speaker recognition: a tutorial→Robust text-independent speaker identification using Gaussian mixture speaker modelsLegacy edge — source detail unavailable
- Distributed Systems: Principles and Paradigms→Introduction to Statistical Pattern RecognitionLegacy edge — source detail unavailable
- Distributed Systems: Principles and Paradigms→Robust text-independent speaker identification using Gaussian mixture speaker modelsLegacy edge — source detail unavailable
- A tutorial on hidden Markov models and selected applications in speech recognition→An introduction to hidden Markov modelsLegacy edge — source detail unavailable
- An overview of text-independent speaker recognition: From features to supervectors→Fundamentals of speech recognitionLegacy edge — source detail unavailable
- An overview of text-independent speaker recognition: From features to supervectors→Robust text-independent speaker identification using Gaussian mixture speaker modelsLegacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Distributed Systems: Principles and Paradigms | 2001 | 2,102 |
| An overview of text-independent speaker recognition: From features to supervectors | 2009 | 1,453 |
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Topics
| Speech Recognition and Synthesis | Computer Science |
| Speech and Audio Processing | Computer Science |
| Music and Audio Processing | Computer Science |
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