Language Recognition using Phone Lattices

Jean‐Luc Gauvain, Abdel Messaoudi, Holger Schwenk

2004 · 43 citations · 0 references

Abstract

This paper proposes a new phone lattice based method for automatic language recognition from speech data. By using phone lattices some approximations usually made by language identification (LID) systems relying on phonotactic constraints to simplify the training and decoding processes can be avoided. We demonstrate the use of phone lattices both in training and testing significantly improves the accuracy of a phonotactically based LID system. Performance is further enhanced by using a neural network to combine the results of multiple phone recog-nizers. Using three phone recognizers with context independent phone models, the system achieves an equal error rate of 2.7% on the Eval03 NIST detection test (30s segment, primary con-dition) with an overall decoding process that runs faster than real-time (0.5xRT). 1.