| 2 |
Investigating alignment interpretability for low-resource NMT
|
|
|
|
In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Is there a bilingual disadvantage for word segmentation? A computational modeling approach
|
|
|
|
In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498905 ; Journal of Child Language, Cambridge University Press (CUP), 2021, pp.1-28. ⟨10.1017/S0305000921000568⟩ (2021)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
SM to: Is there a bilingual disadvantage for word segmentation? A computational modeling approach ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Early Tashelhiyt Berber word segmentation: the role of the Possible Word Constraint ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 6 |
Discovering structure in speech recordings: Unsupervised learning of word and phoneme like units for automatic speech recognition
|
|
|
|
In: Fraunhofer IAIS (2021)
|
|
BASE
|
|
Show details
|
|
|
| 7 |
Handling cross and out-of-domain samples in Thai word segmentation
|
|
|
|
In: 1003 ; 1016 (2021)
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Measuring (online) word segmentation in adults and children
|
|
|
|
In: Dutch Journal of Applied Linguistics, Vol 10 (2021) (2021)
|
|
BASE
|
|
Show details
|
|
|
| 9 |
Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
|
|
|
|
In: Proceedings of the 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020), ; SLTU-CCURL workshop, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02895907 ; SLTU-CCURL workshop, LREC 2020, May 2020, Marseille, France (2020)
|
|
BASE
|
|
Show details
|
|
|
| 10 |
F0 Slope and Mean: Cues to Speech Segmentation in French
|
|
|
|
In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-03042331 ; Interspeech 2020, Oct 2020, Shanghai, China. pp.1610-1614, ⟨10.21437/Interspeech.2020-2509⟩ (2020)
|
|
BASE
|
|
Show details
|
|
|
| 11 |
The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 12 |
Data for: The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 13 |
The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 14 |
Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech
|
|
|
|
BASE
|
|
Show details
|
|
|
| 15 |
Infants Segment Words from Songs—An EEG Study
|
|
|
|
In: Brain Sciences ; Volume 10 ; Issue 1 (2020)
|
|
BASE
|
|
Show details
|
|
|
| 16 |
Not all words are equally acquired: transitional probabilities and instructions affect the electrophysiological correlates of statistical learning
|
|
|
|
BASE
|
|
Show details
|
|
|
| 17 |
Controlling Utterance Length in NMT-based Word Segmentation with Attention
|
|
|
|
In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343206 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China (2019)
|
|
BASE
|
|
Show details
|
|
|
| 18 |
Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus
|
|
|
|
In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-02274050 ; Open Mind, MIT Press, 2019, 3, pp.13-22. ⟨10.1162/opmi_a_00022⟩ (2019)
|
|
BASE
|
|
Show details
|
|
|
| 19 |
Unsupervised word discovery for computational language documentation ; Découverte non-supervisée de mots pour outiller la linguistique de terrain
|
|
|
|
In: https://tel.archives-ouvertes.fr/tel-02286425 ; Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLS062⟩ (2019)
|
|
BASE
|
|
Show details
|
|
|
| 20 |
MiNgMatch—A Fast N-gram Model for Word Segmentation of the Ainu Language
|
|
|
|
In: Information ; Volume 10 ; Issue 10 (2019)
|
|
BASE
|
|
Show details
|
|
|
|
|
