Results 21 to 30 of about 28,490,308 (324)
TeaForN: Teacher-Forcing with N-grams [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Sequence generation models trained with teacher-forcing suffer from issues related to exposure bias and lack of differentiability across timesteps.
Sebastian Goodman +2 more
semanticscholar +1 more source
Verse Search System for Sound Differences in the Qur’an Based on the Text of Phonetic Similarities
Jurnal Sisfokom, 2020 Al-Qur'an has a lot of content, so the system of searching for verses of the Al-Qur’an is needed because if it is done manually it will be difficult. One of the search systems for the verses of the Al-Qur'an in accordance with Indonesia’s pronunciation ...
Agni Octavia +2 more
doaj +1 more source
Positional skipgrams for Bambara: a resource for corpus-based studies
Mandenkan, 2020 This article presents a new online dataset of linguistically rich n‑gram frequency data for Bambara based on the disambiguated part of the Bambara Reference Corpus.
Kirill Maslinsky
doaj +1 more source
Pseudo-Conventional N-Gram Representation of the Discriminative N-Gram Model for LVCSR [PDF]
IEEE Journal of Selected Topics in Signal Processing, 2010 The discriminative n-gram modeling approach re-ranks the N-best hypotheses generated during decoding and can effectively improve the performance of large-vocabulary continuous speech recognition (LVCSR). This work recasts the discriminative n-gram model as a pseudo-conventional n-gram model.
Zhengyu Zhou, Helen M. Meng
openaire +1 more source
Computing n-gram statistics in MapReduce [PDF]
Proceedings of the 16th International Conference on Extending Database Technology, 2013 Statistics about n-grams (i.e., sequences of contiguous words or other tokens in text documents or other string data) are an important building block in information retrieval and natural language processing. In this work, we study how n-gram statistics, optionally restricted by a maximum n-gram length and minimum collection frequency, can be computed ...
Berberich, K., Bedathur, S.
openaire +6 more sources
Diacritics restoration based on word n-grams for Slovak texts
Open Computer Science, 2021 Despite the modern boom in technology, we are still faced with the fact that people write texts without diacritics. There are two main reasons for this.
Toth Štefan +4 more
doaj +1 more source
chrF++: words helping character n-grams
Conference on Machine Translation, 2017 ,
Maja Popovic
semanticscholar +1 more source
Palabras clave en contexto (usando n-grams) con Python
The Programming Historian en Español, 2017 Esta lección retoma los pares de frecuencias recolectados en Contar frecuencias de palabras y crea una salida de datos en HTML.
William J. Turkel, Adam Crymble
doaj +1 more source
An interactive visualization of Google Books Ngrams with R and Shiny: Exploring a(n) historical increase in onset strength in a(n) huge database [PDF]
Journal of Data Mining and Digital Humanities, 2020 Using the re-emergence of the /h/ onset from Early Modern to Present-Day English as a case study, we illustrate the making and the functions of a purpose-built web application named (an:a) lyzer for the interactive visualization of the raw n-gram data ...
Julia Schlüter, Fabian Vetter
doaj +1 more source
N-Gram Representations For Comment Filtering [PDF]
Proceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists, 2015 Accurate classifiers for short texts are valuable assets in many applications. Especially in online communities, where users contribute to content in the form of posts and com- ments, an effective way of automatically categorising posts proves highly valuable.
Dirk Brand +3 more
openaire +3 more sources