Search Results for author:
Found 6 papers, 0 papers with code
The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies
The Reading Machine, is a parsing framework that takes as input raw text and performs six standard nlp tasks: tokenization, pos tagging, morphological analysis, lemmatization, dependency parsing and sentence segmentation.
Using ASR-Generated Text for Spoken Language Modeling
This papers aims at improving spoken language modeling (LM) using very large amount of automatically transcribed speech.
TALEP at CMCL 2021 Shared Task: Non Linear Combination of Low and High-Level Features for Predicting Eye-Tracking Data
In this paper we describe our contribution to the CMCL 2021 Shared Task, which consists in predicting 5 different eye tracking variables from English tokenized text.
ASR-Generated Text for Language Model Pre-training Applied to Speech Tasks
We aim at improving spoken language modeling (LM) using very large amount of automatically transcribed speech.
Dependency Parsing with Backtracking using Deep Reinforcement Learning
Greedy algorithms for NLP such as transition based parsing are prone to error propagation.
Typological Features for Multilingual Delexicalised Dependency Parsing
The existence of universal models to describe the syntax of languages has been debated for decades.
