Project Details
NTT - Speech enhancement front-end for robust automatic speech recognition with large amount of training data
Project Period: 1. 1. 2019 – 31. 12. 2019
Project Type: contract
Partner: NTT Corporation
Czech title
Parametrizace s obohacováním řeči pro robustní automatické rozpoznávání řeči s velkým objemem trénovacích dat
Type
contract
Keywords
speech recognition, robustness, large data, DNN embeddings
Abstract
The purpose of the Joint Research is to develop Speech enhancement front-end for robust automatic speech recognition with large amount of training data through the cooperation of NTT and BUT. The work is relying on embeddings produced by neural networks in various places of the processing chain.
Team members
Publications
2020
- ROHDIN, J.; SILNOVA, A.; DIEZ SÁNCHEZ, M.; PLCHOT, O.; MATĚJKA, P.; BURGET, L.; GLEMBEK, O. End-to-end DNN based text-independent speaker recognition for long and short utterances. COMPUTER SPEECH AND LANGUAGE, 2020, vol. 2020, no. 59,
p. 22-35. ISSN: 0885-2308. Detail
2019
- DELCROIX, M.; ŽMOLÍKOVÁ, K.; OCHIAI, T.; KINOSHITA, K.; ARAKI, S.; NAKATANI, T. Compact Network for Speakerbeam Target Speaker Extraction. In Proceedings of ICASSP. Brighton: IEEE Signal Processing Society, 2019.
p. 6965-6969. ISBN: 978-1-5386-4658-8. Detail - DELCROIX, M.; ŽMOLÍKOVÁ, K.; OCHIAI, T.; KINOSHITA, K.; ARAKI, S.; NAKATANI, T. Evaluation of SpeakerBeam target speech extraction in real noisy and reverberant conditions. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF JAPAN, 2019, vol. 2019, no. 2,
p. 1-2. ISSN: 0369-4232. Detail