A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Transfer learning for speech and language processing
2015
2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)
Transfer learning is a vital technique that generalizes models trained for one setting or task to other settings or tasks. For example in speech recognition, an acoustic model trained for one language can be used to recognize speech in another language, with little or no re-training data. Transfer learning is closely related to multi-task learning (cross-lingual vs. multilingual), and is traditionally studied in the name of 'model adaptation'. Recent advance in deep learning shows that transfer
doi:10.1109/apsipa.2015.7415532
dblp:conf/apsipa/WangZ15
fatcat:oby5enn52batdhoewb4n3ufo4y