A Comparative Pronunciation Mapping Approach Using G2P Conversion for Anglicisms in German Speech Recognition
Abstract
Anglicisms pose a challenge in German speech recognition due to their irregular pronunciation compared to native German words. To solve this issue, we propose a comparative approach that uses both a German and an English grapheme-to-phoneme model to create Anglicism pronunciations. Comparing their confidence measures, we chose the best resulting pronunciations and added them to an Anglicism pronunciation dictionary. We allowed using English pronunciations within a German ASR model by using phoneme mapping to transform English phonemes to their most likely German equivalents. With our approach, we utilize the original pronunciations of the Anglicisms source language while keeping the German Anglicism pronunciations with high accuracy. Tested on a dedicated Anglicism evaluation set, we improved the recognition of Anglicisms compared to a baseline model, reducing the word error rate by 1.33 % relative and the Anglicism error rate by 4.08 % relative.
