Vocabulary and Environment Adaptation in Vocabulary-Independent Speech Recognition

1992 ◽  
Author(s):  
Hsiao-Wuen Hon ◽  
Kai-Fu Lee
Keyword(s):  
Speech Recognition ◽  
Environment Adaptation

scholarly journals Rapid environment adaptation for speech recognition.

1995 ◽  
Vol 16 (5) ◽  
pp. 273-281 ◽  
Author(s):  
Keizaburo Takagi ◽  
Hiroaki Hattori ◽  
Takao Watanabe
Keyword(s):  
Speech Recognition ◽  
Environment Adaptation

scholarly journals Transfer learning for domain and environment adaptation in Serbian ASR

2020 ◽  
Vol 12 (2) ◽  
pp. 110-115
Author(s):  
Branislav Popović ◽  
Edvin Pakoci ◽  
Darko Pekar
Keyword(s):  
Speech Recognition ◽  
Transfer Learning ◽  
Error Rate ◽  
System Development ◽  
Training Data ◽  
Similar Data ◽  
Noisy Environment ◽  
Word Error Rate ◽  
Environment Adaptation ◽  
Speech Database

In automatic speech recognition systems, the training data used for system development and the data actually obtained from the users of the system sometimes significantly differ in practice. However, other, more similar data may be available. Transfer learning can help to exploit such similar data for training in order to boost the automatic speech recognizer's performance for a certain domain. This paper presents a few applications of transfer learning in the context of speech recognition, specifically for the Serbian language. Several methods are proposed, with the goal of optimizing system performance on a specific part of the existing speech database for Serbian, or in a noisy environment. The experimental results evaluated on a test set from the desired domain show significant improvement in both word error rate and character error rate.

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