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Found 25 papers, 3 papers with code
Identification des Expressions Polylexicales dans les Tweets (Identification of Multiword Expressions in Tweets)
L’identification des expressions polylexicales (EP) dans les tweets est une tâche difficile en raison de la nature linguistique complexe des EP combinée à l’utilisation d’un langage non standard.
Identification of Multiword Expressions in Tweets for Hate Speech Detection
In this article, we present joint experiments on these two related tasks on English Twitter data: first we focus on the MWE identification task, and then we observe the influence of MWE-based features on the HSD task.
Unsupervised Domain Adaptation in Cross-corpora Abusive Language Detection
The state-of-the-art abusive language detection models report great in-corpus performance, but underperform when evaluated on abusive comments that differ from the training scenario.
Label Propagation-Based Semi-Supervised Learning for Hate Speech Classification
In this paper, label propagation-based semi-supervised learning is explored for the task of hate speech classification.
Generalisability of Topic Models in Cross-corpora Abusive Language Detection
Rapidly changing social media content calls for robust and generalisable abuse detection models.
Transferring Knowledge via Neighborhood-Aware Optimal Transport for Low-Resource Hate Speech Detection
The concerning rise of hateful content on online platforms has increased the attention towards automatic hate speech detection, commonly formulated as a supervised classification task.
Domain Classification-based Source-specific Term Penalization for Domain Adaptation in Hate-speech Detection
State-of-the-art approaches for hate-speech detection usually exhibit poor performance in out-of-domain settings.
Placing M-Phasis on the Plurality of Hate: A Feature-Based Corpus of Hate Online
Even though hate speech (HS) online has been an important object of research in the last decade, most HS-related corpora over-simplify the phenomenon of hate by attempting to label user comments as "hate" or "neutral".
Dynamically Refined Regularization for Improving Cross-corpora Hate Speech Detection
In this paper, we propose to automatically identify and reduce spurious correlations using attribution methods with dynamic refinement of the list of terms that need to be regularized during training.
Improving Automatic Hate Speech Detection with Multiword Expression Features
To incorporate MWE features, we create a three-branch deep neural network: one branch for USE, one for MWE categories, and one for MWE embeddings.
DNN-Based Semantic Model for Rescoring N-best Speech Recognition List
We propose to perform this through rescoring of the ASR N-best hypotheses list.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Reconnaissance automatique de la parole : g\'en\'eration des prononciations non natives pour l'enrichissement du lexique (In this study we propose a method for lexicon adaptation in order to improve the automatic speech recognition (ASR) of non-native speakers)
Pour prendre en compte ce probl{\`e}me de prononciations erron{\'e}es, notre approche propose d{'}int{\'e}grer les prononciations non natives dans le lexique et par la suite d{'}utiliser ce lexique enrichi pour la reconnaissance.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Introduction d'informations s\'emantiques dans un syst\`eme de reconnaissance de la parole (Despite spectacular advances in recent years, the Automatic Speech Recognition (ASR) systems still make mistakes, especially in noisy environments)
Malgr{\'e} les avanc{\'e}s spectaculaires ces derni{\`e}res ann{\'e}es, les syst{\`e}mes de Reconnaissance Automatique de Parole (RAP) commettent encore des erreurs, surtout dans des environnements bruit{\'e}s. Pour am{\'e}liorer la RAP, nous proposons de se diriger vers une contextualisation d{'}un syst{\`e}me RAP, car les informations s{\'e}mantiques sont importantes pour la performance de la RAP.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Projet AMIS : r\'esum\'e et traduction automatique de vid\'eos (AMIS project : automatic summarization and translation of videos)
Un autre objectif du projet {\'e}tait aussi de comparer les opinions et sentiments exprim{\'e}s dans plusieurs vid{\'e}os comparables.
Towards non-toxic landscapes: Automatic toxic comment detection using DNN
The contribution of this paper is the design of binary classification and regression-based approaches aiming to predict whether a comment is toxic or not.
An enhanced automatic speech recognition system for Arabic
Despite all the classical techniques for Automatic Speech Recognition (ASR), which can be efficiently applied to Arabic speech recognition, it is essential to take into consideration the language specificities to improve the system performance.
Weakly-supervised text-to-speech alignment confidence measure
This work proposes a new confidence measure for evaluating text-to-speech alignment systems outputs, which is a key component for many applications, such as semi-automatic corpus anonymization, lips syncing, film dubbing, corpus preparation for speech synthesis and speech recognition acoustic models training.
How Diachronic Text Corpora Affect Context based Retrieval of OOV Proper Names for Audio News
Out-Of-Vocabulary (OOV) words missed by Large Vocabulary Continuous Speech Recognition (LVCSR) systems can be recovered with the help of topic and semantic context of the OOV words captured from a diachronic text corpus.
The IFCASL Corpus of French and German Non-native and Native Read Speech
The IFCASL corpus is a French-German bilingual phonetic learner corpus designed, recorded and annotated in a project on individualized feedback in computer-assisted spoken language learning.
Learning to retrieve out-of-vocabulary words in speech recognition
In this paper, we propose two neural network models targeted to retrieve OOV PNs relevant to an audio document: (a) Document level Continuous Bag of Words (D-CBOW), (b) Document level Continuous Bag of Weighted Words (D-CBOW2).
Designing a Bilingual Speech Corpus for French and German Language Learners: a Two-Step Process
We present the design of a corpus of native and non-native speech for the language pair French-German, with a special emphasis on phonetic and prosodic aspects.
CoALT: A Software for Comparing Automatic Labelling Tools
In this paper, we propose a GPL software CoALT (Comparing Automatic Labelling Tools) for comparing two automatic labellers or two speech-text alignment tools, ranking them and displaying statistics about their differences.
