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
Žmolíková Kateřina, Ing., Ph.D. (FIT) – research leader
Černocký Jan, prof. Dr. Ing. (DCGM)
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
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