This paper investigates lexical stress detection for L2 English speech using Deep Belief Networks (DBNs). The features of the DBN used in this work include ...
This paper investigates lexical stress detection for L2 English speech using Deep Belief Networks (DBNs). The features of the DBN used in this work include ...
This paper investigates lexical stress detection for L2 English speech using Deep Belief Networks (DBNs) and achieves an accuracy of about 80% in syllable ...
This paper investigates lexical stress detection for L2 English speech using Deep Belief Networks (DBNs). The features of the DBN used in this work include ...
Kun Li, Xiaojun Qian, Shiyin Kang, Helen Meng: Lexical stress detection for L2 English speech using deep belief networks. INTERSPEECH 2013: 1811-1815.
This paper investigates the use of multi-distribution deep neural networks (MD-DNNs) for automatic lexical stress detection and pitch accent detection.
This paper investigates lexical stress detection for L2 English speech using Deep Belief Networks (DBNs) and achieves an accuracy of about 80% in syllable ...
This paper investigates the use of multi-distribution deep neural networks (MD-DNNs) for automatic lexical stress detection and pitch accent detection, ...
Nov 6, 2019 · ABSTRACT. The dominant automatic lexical stress detection method is to split the utterance into syllable segments using phoneme.
People also ask
How do you identify lexical stress?
Does English have lexical stress?
This paper describes two novel complementary techniques that improve the detection of lexical stress errors in non-native. (L2) English speech: ...