- Adnene Zairi, A. Waibel, Kevin Kilgour. 2015. Sub-word Language Models for German LVCSR. Abstract: This work is devoted to build sub-word language models for German Large Vocabulary Continuous Speech Recognition (LVCSR) Systems. The motivation of using a sub-words based system comes from its ability to model unseen compound words in the training corpus by compounding sequences of sub-units forming new words. The two techniques we apply for the generation of sub-words, are based on syllables and letter n-grams. In three scenarios, we investigate different techniques acting on the input split vocabulary and the vocabulary for the language model and the pronunciation dictionary. Using a combination of full-words and syllables from the training corpus presents the most efficient split method, which also leads to the best word error rate (WER) results during the decoding task. This split method consists on keeping the most frequent words in the training corpus and splitting the infrequent ones into syllables or characters.
