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- W2507324877 abstract "In the phonotactic approach for language recognition, a phonetokeniser is normally used to transform the audio signal intoacoustic tokens. The language identity of the speech is modelledby the occurrence statistics of the decoded tokens. Theperformance of this approach depends heavily on the quality ofthe audio tokeniser. A high-quality tokeniser in matched conditionis not always available for a language recognition task.This study investigated into the performance of a phonotacticlanguage recogniser in a resource-constrained setting, followingNIST LRE 2015 specification. An ensemble of phone tokeniserswas constructed by applying unsupervised sequence trainingon different target languages followed by a score-based fusion.This method gave 5−7% relative performance improvement tobaseline system on LRE 2015 eval set. This gain was retainedwhen the ensemble phonotactic system was further fused withan acoustic iVector system" @default.
- W2507324877 created "2016-09-16" @default.
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- W2507324877 date "2016-09-08" @default.
- W2507324877 modified "2023-09-27" @default.
- W2507324877 title "Combining Weak Tokenisers for Phonotactic Language Recognition in a Resource-Constrained Setting" @default.
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- W2507324877 doi "https://doi.org/10.21437/interspeech.2016-630" @default.
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