Improved automatic language identification in noisy speech
Fred J. Goodman, Arnaud Martin, R. E. Wohlford · International Conference on Acoustics, Speech, and Signal Processing · 2003
A description is given of enhancements to an automatic language identification algorithm previously reported. The algorithm, based on linear-predictive-coding-based formant extraction, was greatly improved, reducing the error rate by more than 50%. This performance was achieved on a large (>9 h), very noisy, six-language database, using trials of less than 10 s. Experiments that improved performance are described, including tests of various distance metrics, expanded and modified parameter sets, and a new voicing statistic. Final performance results were obtained as a function of time, signal-to-noise ratio, and no-decision rate. A new rejection capability was developed to address the open-set identification problem.>