The conventional i-vector approach to speaker and language recognition constitutes an
unsupervised learning paradigm where a variable length speech utterance is converted into …

The language cue is an important component in the task of spoken language identification
(LID). But it will take a lot of time to align language cue to speech segment by the manual …

Correlated speech tasks can learn related information from each other to enhance the
performance. In this paper, a unified model based on end-to-end DNN and multi-task …

A novel language identification (LID) method is proposed that accepts the architecture of
time delay neural network (TDNN) followed by long short term memory (LSTM) recurrent …

In the age of artificial intelligence, it is important for machines to figure out who is speaking
automatically and in what language-a task humans are naturally capable of. Developing …

Language identification is quite challenging when it comes to discriminating between
closely related dialects of the same language. The fundamental issue is to explore the …

The discriminative cues and effective representations are two important factors for spoken
language identification (LID). In this paper, the multi-levels language cues, including …