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Found 24 papers, 3 papers with code
Findings of the First Shared Task on Lifelong Learning Machine Translation
A lifelong learning system can adapt to new data without forgetting previously acquired knowledge.
Analyzing BERT Cross-lingual Transfer Capabilities in Continual Sequence Labeling
Knowledge transfer between neural language models is a widely used technique that has proven to improve performance in a multitude of natural language tasks, in particular with the recent rise of large pre-trained language models like BERT.
Attention Modulation for Zero-Shot Cross-Domain Dialogue State Tracking
Dialog state tracking (DST) is a core step for task-oriented dialogue systems aiming to track the user’s current goal during a dialogue.
A Textless Metric for Speech-to-Speech Comparison
In this paper, we introduce a new and simple method for comparing speech utterances without relying on text transcripts.
Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding
On-the-job learning consists in continuously learning while being used in production, in an open environment, meaning that the system has to deal on its own with situations and elements never seen before.
\'Evaluation de syst\`emes apprenant tout au long de la vie (Evaluation of lifelong learning systems )
Une adaptation de leur mod{\`e}le par des experts en apprentissage automatique est possible mais tr{\`e}s co{\^u}teuse alors que les soci{\'e}t{\'e}s utilisant ces syst{\`e}mes disposent d{'}experts du domaine qui pourraient accompagner ces syst{\`e}mes dans un apprentissage tout au long de la vie.
Evaluation of Lifelong Learning Systems
Current intelligent systems need the expensive support of machine learning experts to sustain their performance level when used on a daily basis.
Analyzing Learned Representations of a Deep ASR Performance Prediction Model
In a previous paper, we presented an ASR performance prediction system using CNNs that encode both text (ASR transcript) and speech, in order to predict word error rate.
ASR Performance Prediction on Unseen Broadcast Programs using Convolutional Neural Networks
In this paper, we address a relatively new task: prediction of ASR performance on unseen broadcast programs.
Estimation de la qualit\'e d'un syst\`eme de reconnaissance de la parole pour une t\^ache de compr\'ehension (Quality estimation of a Speech Recognition System for a Spoken Language Understanding task)
Nous comparons ici diff{\'e}rentes m{\'e}triques, notamment le WER, NE-WER et ATENE m{\'e}trique propos{\'e}e r{\'e}cemment pour l{'}{\'e}valuation des syst{\`e}mes de reconnaissance de la parole {\'e}tant donn{\'e} une t{\^a}che de reconnaissance d{'}entit{\'e}s nomm{\'e}es.
Comparaison de listes d'erreurs de transcription automatique de la parole : quelle compl\'ementarit\'e entre les diff\'erentes m\'etriques ? (Comparing error lists for ASR systems : contribution of different metrics)
Le travail que nous pr{\'e}sentons ici s{'}inscrit dans le domaine de l{'}{\'e}valuation des syst{\`e}mes de reconnaissance automatique de la parole en vue de leur utilisation dans une t{\^a}che aval, ici la reconnaissance des entit{\'e}s nomm{\'e}es.
LNE-Visu : a tool to explore and visualize multimedia data
LNE-Visu : a tool to explore and visualize multimedia data LNE-Visu is a tool to explore and visualize multimedia data created for the LNE evaluation campaigns.
Generating Task-Pertinent sorted Error Lists for Speech Recognition
In the context of Automatic Speech Recognition (ASR) used as a first step towards Named Entity Recognition (NER) in speech, error seriousness is usually determined by their frequency, due to the use of the WER as metric to evaluate the ASR output, despite the emergence of more relevant measures in the literature.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
The ETAPE speech processing evaluation
The ETAPE evaluation is the third evaluation in automatic speech recognition and associated technologies in a series which started with ESTER.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
ETER : a new metric for the evaluation of hierarchical named entity recognition
We then introduce a new metric, the Entity Tree Error Rate (ETER), to evaluate hierarchical and structured named entity detection, classification and decomposition.
The ETAPE corpus for the evaluation of speech-based TV content processing in the French language
The paper presents a comprehensive overview of existing data for the evaluation of spoken content processing in a multimedia framework for the French language.
The REPERE Corpus : a multimodal corpus for person recognition
In this context, the REPERE corpus, a French videos corpus with multimodal annotation, has been developed.
Analyzing the Impact of Prevalence on the Evaluation of a Manual Annotation Campaign
This article details work aiming at evaluating the quality of the manual annotation of gene renaming couples in scientific abstracts, which generates sparse annotations.
Extended Named Entities Annotation on OCRed Documents: From Corpus Constitution to Evaluation Campaign
Within the framework of the Quaero project, we proposed a new definition of named entities, based upon an extension of the coverage of named entities as well as the structure of those named entities.
Named Entity Recognition (NER)
Optical Character Recognition (OCR)
