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20172022
most citedData augmentation using prosody and false starts to recognize non-native children's speech

15 citations · 21 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.CL2020

FinChat: Corpus and evaluation setup for Finnish chat conversations on everyday topics

Katri Leino, Juho Leinonen, Mittul Singh +2

Creating open-domain chatbots requires large amounts of conversational data and related benchmark tasks to evaluate them. Standardized evaluation tasks are crucial for creating aut…

cs.CL2020

Effects of Language Relatedness for Cross-lingual Transfer Learning in Character-Based Language Models

Mittul Singh, Peter Smit, Sami Virpioja +1

Character-based Neural Network Language Models (NNLM) have the advantage of smaller vocabulary and thus faster training times in comparison to NNLMs based on multi-character units.…

cs.CL20205 cited

Subword RNNLM Approximations for Out-Of-Vocabulary Keyword Search

Mittul Singh, Sami Virpioja, Peter Smit +1

In spoken Keyword Search, the query may contain out-of-vocabulary (OOV) words not observed when training the speech recognition system. Using subword language models (LMs) in the f…

cs.CL2019

Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling

Debjit Paul, Mittul Singh, Michael A. Hedderich +1

In this paper, we address the problem of effectively self-training neural networks in a low-resource setting. Self-training is frequently used to automatically increase the amount…

cs.CL2017

Long-Short Range Context Neural Networks for Language Modeling

Youssef Oualil, Mittul Singh, Clayton Greenberg +1

The goal of language modeling techniques is to capture the statistical and structural properties of natural languages from training corpora. This task typically involves the learni…

cs.CL2017

Sequential Recurrent Neural Networks for Language Modeling

Youssef Oualil, Clayton Greenberg, Mittul Singh +1

Feedforward Neural Network (FNN)-based language models estimate the probability of the next word based on the history of the last N words, whereas Recurrent Neural Networks (RNN) p…