MLLP-UPV and RWTH Aachen Spanish ASR Systems for the IberSpeech-RTVE 2018 Speech-to-Text Transcription Challenge

Javier Jorge, Adrià Martínez-Villaronga, Pavel Golik, Adrià Giménez, Joan Albert Silvestre-Cerdà, Patrick Doetsch, Vicent Andreu Císcar, Hermann Ney, Alfons Juan, Albert Sanchis


This paper describes the Automatic Speech Recognition systems built by the MLLP research group of Universitat Politècnica de València and the HLTPR research group of RWTH Aachen for the IberSpeech-RTVE 2018 Speech-to-Text Transcription Challenge. We participated in both the closed and the open training conditions. The best system built for the closed condition was an hybrid BLSTM-HMM ASR system using one-pass decoding with a combination of a RNN LM and show-adapted n-gram LMs. It was trained on a set of reliable speech data extracted from the train and dev1 sets using MLLP's transLectures-UPV toolkit (TLK) and TensorFlow. This system achieved 20.0% WER on the dev2 set. For the open condition we used approx. 3800 hours of out-of-domain training data from multiple sources and trained a one-pass hybrid BLSTM-HMM ASR system using open-source tools RASR and RETURNN developed at RWTH Aachen. This system scored 15.6% WER on the dev2 set. The highlights of these systems include robust speech data filtering for acoustic model training and show-specific language modeling.


 DOI: 10.21437/IberSPEECH.2018-54

Cite as: Jorge, J., Martínez-Villaronga, A., Golik, P., Giménez, A., Silvestre-Cerdà, J.A., Doetsch, P., Císcar, V.A., Ney, H., Juan, A., Sanchis, A. (2018) MLLP-UPV and RWTH Aachen Spanish ASR Systems for the IberSpeech-RTVE 2018 Speech-to-Text Transcription Challenge. Proc. IberSPEECH 2018, 257-261, DOI: 10.21437/IberSPEECH.2018-54.


@inproceedings{Jorge2018,
  author={Javier Jorge and Adrià Martínez-Villaronga and Pavel Golik and Adrià Giménez and Joan Albert Silvestre-Cerdà and Patrick Doetsch and Vicent Andreu Císcar and Hermann Ney and Alfons Juan and Albert Sanchis},
  title={{MLLP-UPV and RWTH Aachen Spanish ASR Systems for the IberSpeech-RTVE 2018 Speech-to-Text Transcription Challenge}},
  year=2018,
  booktitle={Proc. IberSPEECH 2018},
  pages={257--261},
  doi={10.21437/IberSPEECH.2018-54},
  url={http://dx.doi.org/10.21437/IberSPEECH.2018-54}
}