Abstract:
The paper describes Brno University of Technology (BUT) ASR system for 2014 BABEL Surprise language evaluation (Tamil). While being largely based on our previous work, tw...Show MoreMetadata
Abstract:
The paper describes Brno University of Technology (BUT) ASR system for 2014 BABEL Surprise language evaluation (Tamil). While being largely based on our previous work, two original contributions were brought: (1) speaker-adapted bottle-neck neural network (BN) features were investigated as an input to DNN recognizer and semi-supervised training was found effective. (2) Adding of noise to training data outperformed a classical de-noising technique while dealing with noisy test data was found beneficial, and the performance of this approach was verified on a relatively clean training/test data setup from a different language. All results are reported on BABEL 2014 Tamil data.
Published in: 2014 IEEE Spoken Language Technology Workshop (SLT)
Date of Conference: 07-10 December 2014
Date Added to IEEE Xplore: 02 April 2015
Electronic ISBN:978-1-4799-7129-9