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1
Effective keyword search for low-resourced conversational speech
In: icassp 2017 ; https://hal.archives-ouvertes.fr/hal-01744176 ; icassp 2017, IEEE, Mar 2017, La Nouvelle Orléans, United States (2017)
Abstract: International audience ; In this paper we aim to enhance keyword search for conversational telephone speech underlow-resourced conditions. Two techniques to improve the detection of out-of-vocabularykeywords are assessed in this study: using extra text resources to augment the lexicon andlanguage model, and via subword units for keyword search. Two approaches for dataaugmentation are explored to extend the limited amount of transcribed conversationalspeech: using conversational-like Web data and texts generated by recurrent neuralnetworks. Contrastive comparisons of subword-based systems are performed to evaluatethe benefits of multiple subword decodings and single decoding. Keyword search results arereported for all the techniques, but only some improve performance. Results are reported forthe Mongolian and Igbo languages using data from the 2016 Babel program.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; keyword search; language modeling; low-resourced languages; Speech recognition; text augmentation
URL: https://hal.archives-ouvertes.fr/hal-01744176
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2
An investigation into language model data augmentation for low-resourced STT and KWS
In: IEEE International Conference on Acoustics, Speech, and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01837171 ; IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, Mar 2017, New Orleans, United States (2017)
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3
Language Model Data Augmentation for Keyword Spotting
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01837186 ; Annual Conference of the International Speech Communication Association , Jan 2016, San Francisco, United States (2016)
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