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German Speech Recognition using Kaldi

Scripts to train Kaldi model for German speech recognition.

Data / LM / Lexicon

First, we have to get the data, a language model and the lexicon.

Preparation

Before training, preparation of data, lexicon and lm has to be done by executing the script prepare.sh. In order to do that some python dependencies have to be installed with pip install -r requirements.

./prepare.sh \
    [german-asr-data]/data/full_waverized \
    [lexicon] \
    [sequitur-model] \
    [lm]

Training

After preparation, the actual training is done. At this step kaldi is used. To run it the easiest was is to used the docker image from https://hub.docker.com/r/kaldiasr/kaldi. All commands are in run.sh. This script is derived from the LibriSpeech recipe at egs/librispeech.

Results

Word error rates in %, for megs v2.

Model Training-Data dev test
tdnn-chain train 14.12 15.42
Model Training-Data dev_cv test_cv dev_tuda test_tuda
tdnn-chain train 14.71 18.45 11.85 12.80
Model Training-Data dev_swc test_swc dev_voxforge test_voxforge
tdnn-chain train 18.74 17.45 7.78 8.25