Cross-lingual articulation information transfer with progressive networks for speech recognition
Morshed, Mahir
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Permalink
https://hdl.handle.net/2142/115607
Description
Title
Cross-lingual articulation information transfer with progressive networks for speech recognition
Author(s)
Morshed, Mahir
Issue Date
2022-04-29
Director of Research (if dissertation) or Advisor (if thesis)
Hasegawa-Johnson, Mark A
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
articulatory feature detection
transfer learning
progressive neural networks
Abstract
A system for the lateral transfer of information from recurrent end-to-end neural networks recognizing articulatory feature classes to similarly structured networks recognizing phone tokens is proposed. The system uses connections between recurrent layers at the same depth between feature detectors pre-trained on a base language and a phone recognizer for different target languages, inspired primarily by the progressive neural network scheme. While initial experiments using detectors for four articulatory feature classes—consonant place, consonant manner, vowel height, and vowel backness—trained on Bengali speech, attached to phone recognizers for four other Asian languages (Javanese, Nepali, Sinhalese, Sundanese), do not currently suggest consistent performance improvements across different low-resource settings for target languages, irrespective of their genealogic or phonological relatedness to Bengali, they do suggest the need for further trials with different language sets, altered data sources and data configurations, and slightly altered network setups.
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