COMPARISON OF OPTIMIZATION ALGORITHMS OF CONNECTIONIST TEMPORAL CLASSIFIER FOR SPEECH RECOGNITION SYSTEM
Yedilkhan Amirgaliyev
amir_ed@mail.ru1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan (Kazakhstan)
http://orcid.org/0000-0002-6528-0619
Kuanyshbay Kuanyshbay
1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan (Kazakhstan)
http://orcid.org/0000-0001-5952-8609
Aisultan Shoiynbek
1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan (Kazakhstan)
http://orcid.org/0000-0002-9328-8300
Abstract
This paper evaluates and compares the performances of three well-known optimization algorithms (Adagrad, Adam, Momentum) for faster training the neural network of CTC algorithm for speech recognition. For CTC algorithms recurrent neural network has been used, specifically Long-Short-Term memory. LSTM is effective and often used model. Data has been downloaded from VCTK corpus of Edinburgh University. The results of optimization algorithms have been evaluated by the Label error rate and CTC loss.
Keywords:
recurrent neural network, search methods, acoustic, systems modeling languageReferences
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Authors
Yedilkhan Amirgaliyevamir_ed@mail.ru
1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan Kazakhstan
http://orcid.org/0000-0002-6528-0619
Authors
Kuanyshbay Kuanyshbay1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan Kazakhstan
http://orcid.org/0000-0001-5952-8609
Authors
Aisultan Shoiynbek1 Institute Information and Computational Technologies CS MES RK, Almaty, Kazakhstan, 2 Suleyman Demirel University, Almaty, Kazakhstan Kazakhstan
http://orcid.org/0000-0002-9328-8300
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