8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Foreign-Accented Speaker-Independent Speech Recognition

Stefanie Aalburg, Harald Hoege

Siemens AG, Germany

This research investigated whether acoustic-phonetic knowledge of the mother tongue of a non-native speaker can be used to adapt an existing target language phoneme HMM recognizer. For this purpose three sets of phoneme HMMs were generated, one representing the target language (German), one the mother tongue of the non-native speaker (Turkish), and the third the foreign-accented pronunciation of the target language (German spoken by Turkish speakers). The latter served as a benchmark for the tested adaptation methods. A derived Hidden Markov Model (HMM) clustering algorithm was applied on the target language phoneme HMM set using the mother tongue phoneme HMM set of the non-native speaker. Following the HMM adaptation a phoneme-level pronunciation technique was applied to generate phoneme mapping rules for the lexicon adaptation task. The results revealed a relative reduction of about 6% in WER for the adapted HMM. No further improvements were observed from the lexicon adaptation task.

Full Paper

Bibliographic reference.  Aalburg, Stefanie / Hoege, Harald (2004): "Foreign-accented speaker-independent speech recognition", In INTERSPEECH-2004, 1465-1468.