<> "The repository administrator has not yet configured an RDF license."^^ . <> . . . "An Investigation of Word Embeddings with Deep Bidirectional LSTM for Sentence Unit Detection in Automatic Speech Transcription"^^ . "This work investigates the effectiveness of using the word based and sub-word based embedding representations as input for a deep bidirectional Long Short-Term Memory Network for Sentence Unit Detection in Automatic Speech Recognition transcription. Our experimental results show that using sub-word based embedding can significantly improve the SUD performance when a limited text is used to train both the word embedding and the SUD model. The SUD model using the sub-word based embedding gains up to 2.07% absolute improvement in F1-score as compared to the best model trained with the word-based embedding. When tested on a domain-mismatch condition, the SUD model with sub-word based embedding trained from the in-domain data gives an approximate 2% and 1% improvement over the best model using out-of-domain embedding with reference and ASR transcription with 29.5% Word Error Rate respectively."^^ . "2018-11" . . . . . . . . . . . . . . "Duy Cat"^^ . "Can"^^ . "Duy Cat Can"^^ . . "Thi Nga"^^ . "Ho"^^ . "Thi Nga Ho"^^ . . "Eng Siong"^^ . "Chng"^^ . "Eng Siong Chng"^^ . . . . "International Conference on Asian Language Processing (IALP 2018)"^^ . . . . . "Bandung, Indonesia"^^ . . . . . . "An Investigation of Word Embeddings with Deep Bidirectional LSTM for Sentence Unit Detection in Automatic Speech Transcription (PDF)"^^ . . . . "HTML Summary of #3170 \n\nAn Investigation of Word Embeddings with Deep Bidirectional LSTM for Sentence Unit Detection in Automatic Speech Transcription\n\n" . "text/html" . . . "Information Technology (IT)"@en . .