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This paper describes improvements to an innovative high-performance speaker recognition system. Recent experiments showed that with sufficient training data phone strings from multiple languages are exceptional features for speaker recognition. The prototype phonetic speaker recognition system used phone sequences from six languages to produce an equal(More)
This paper describes a newly realized high-performance speaker recognition system and examines methods for its improvement. Innovative experiments early this year showed that phone strings are exceptional features for speaker recognition. The original system produced equal error rates less than 11.5% on Switchboard-I audio files. Subsequent research(More)
Short-time spectral characterizations of the human voice have proven to be the most dependable features available to modern speaker recognition systems. However, it is well-known that highlevel linguistic information such as word usage and pronunciation patterns can provide complementary discriminative power. In an automatic setting, the availability of(More)
In 2015 NIST coordinated the first language recognition evaluation (LRE) that used i-vectors as input, with the goals of attracting researchers outside of the speech processing community to tackle the language recognition problem, exploring new ideas in machine learning for use in language recognition, and improving recognition accuracy. The Language(More)
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