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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)
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2
Developing an Embosi (Bantu C25) Speech Variant Dictionary to Model Vowel Elision and Morpheme Deletion
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01837178 ; Annual Conference of the International Speech Communication Association , ISCA, Aug 2017, Stockholm, Sweden (2017)
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3
Schwa Realization in French: Using Automatic Speech Processing to Study Phonological and Socio-linguistic Factors in Large Corpora
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01837179 ; Annual Conference of the International Speech Communication Association , ISCA, Aug 2017, Stockholm, Sweden (2017)
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4
Addressing Code-Switching in French/Algerian Arabic Speech
In: Interspeech 2017 ; https://halshs.archives-ouvertes.fr/halshs-01969148 ; Interspeech 2017, Aug 2017, Stockholm, Sweden. pp.62-66, ⟨10.21437/interspeech.2017-1373⟩ (2017)
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5
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)
Abstract: International audience ; This paper reports on investigations using two techniques for language model text dataaugmentation for low-resourced automatic speech recognition and keyword search. Low-resourced languages are characterized by limited training materials, which typically resultsin high out-of-vocabulary (OOV) rates and poor language model estimates. One techniquemakes use of recurrent neural networks (RNNs) using word or subword units. Word-basedRNNs keep the same system vocabulary, so they cannot reduce the OOV, whereas subwordunits can reduce the OOV but generate many false combinations. A complementarytechnique is based on automatic machine translation, which requires parallel texts and isable to add words to the vocabulary. These methods were assessed on 10 languages in thecontext of the Babel program and NIST OpenKWS evaluation. Although improvements vary across languages with both methods, small gains were generally observed in terms of word error rate reduction and improved keyword search performance.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO]Computer Science [cs]; keyword search; low resourced languages; multilingual; speech recognition
URL: https://hal.archives-ouvertes.fr/hal-01837171
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6
Addressing Code-Switching in French/Algerian Arabic Speech
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01837206 ; Annual Conference of the International Speech Communication Association , ISCA, Aug 2017, Stockholm, Sweden (2017)
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7
Corpus base linguistic exploration via forced alignments with a ‘light-weight’ ASR tool
In: Language & Technology Conference : Human Language Technologies as a Challenge for Computer Science and Linguistics ; https://hal.archives-ouvertes.fr/hal-01837174 ; Language & Technology Conference : Human Language Technologies as a Challenge for Computer Science and Linguistics, Nov 2017, Poznań, Poland (2017)
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8
Discovering speech reductions across speaking styles and languages
In: Rethinking reduction: Interdisciplinary perspectives on conditions, mechanisms, and domains for phonetic variation ; https://halshs.archives-ouvertes.fr/halshs-01507312 ; Cangemi, F., Clayards M., Niebuhr O., Schuppler B., & Zellers M. Rethinking reduction: Interdisciplinary perspectives on conditions, mechanisms, and domains for phonetic variation, De Gruyter Mouton 2017 (2017)
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9
Phonetic variation and contrast neutralization patterns in Romanian fricatives accross different speaking styles
In: Diversity and Speech Dynamics ; https://hal.archives-ouvertes.fr/hal-01837181 ; Diversity and Speech Dynamics, May 2017, Herrsching am Ammersee, Germany (2017)
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10
Multimodal emotion recognition for AVEC 2016 challenge
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