A reproduction of Apple's bi-directional LSTM models for language identification in short strings

Language Identification is the task of identifying a document's language. For applications like automatic spell checker selection, language identification must use very short strings such as text message fragments... (read more)

PDF Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Language Identification OpenSubtitles Apple bi-LSTM Accuracy 91.37 # 1
Language Identification Universal Dependencies Apple bi-LSTM Accuracy 86.93 # 1

Methods used in the Paper


METHOD TYPE
Sigmoid Activation
Activation Functions
Tanh Activation
Activation Functions
LSTM
Recurrent Neural Networks
BiLSTM
Bidirectional Recurrent Neural Networks