Title :
A syllable-based Turkish speech recognition system by using time delay neural networks (TDNNs)
Author :
Can, Burcu ; Artuner, Harun
Author_Institution :
Dept. of Comput. Eng., Hacettepe Univ., Ankara, Turkey
Abstract :
In this paper, we present a model for Turkish speech recognition. The model is syllable-based, where the recognition is performed through syllables as speech recognition units. The main goal of the model is to recognize as much as possible of a given continuous speech by identifying only a small set of syllables in the language. For that purpose, only the syllable types with a higher frequency are selected for the recognition. The use of longer recognition units in speech recognition systems increases the success of the recognition since it is easier to detect the endpoints of syllables when compared to phonemes. On the other side, word-based recognition requires a very large dataset that includes all the words and word forms in the language, which is also another challenge. Hereby, we take the advantage of Turkish being an ortographically transparent and syllabified language. Our model employs time delay neural networks (TDNNs) for learning syllables. We achieve an accuracy of %65.6 on our large vocabulary continuous speech corpus. In addition, we define an algorithm for the automatic detection of syllable boundaries which gives an accuracy of %44. The automatic syllable boundary detection module is used for the recognition of isolated syllables rather than a continuous speech.
Keywords :
neural nets; speech recognition; TDNN; automatic syllable boundary detection module; ortographically transparent language; speech recognition units; syllabified language; syllable-based Turkish speech recognition system; time delay neural networks; Accuracy; Feature extraction; Neural networks; Speech; Speech recognition; Training; Vectors; artificial intelligence; artificial neural networks; machine learning; speech recognition; syllable-based speech recognition; time-delay neural networks;
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2013 International Conference of
Conference_Location :
Hanoi
Print_ISBN :
978-1-4799-3399-0
DOI :
10.1109/SOCPAR.2013.7054130