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Found 14 papers, 2 papers with code
Killing two birds with one stone: Can an audio captioning system also be used for audio-text retrieval?
For ATR, we propose using the standard Cross-Entropy loss values obtained for any audio/caption pair.
Is my automatic audio captioning system so bad? spider-max: a metric to consider several caption candidates
For this reason, several complementary metrics, such as BLEU, CIDEr, SPICE and SPIDEr, are used to compare a single automatic caption to one or several captions of reference, produced by a human annotator.
Audio-video fusion strategies for active speaker detection in meetings
In this paper, we propose two different types of fusion for the detection of the active speaker, combining two visual modalities and an audio modality through neural networks.
End-to-end acoustic modelling for phone recognition of young readers
Through transfer learning, a Transformer model complemented with a Connectionist Temporal Classification (CTC) objective function, reaches a phone error rate of 28. 1%, outperforming a state-of-the-art DNN-HMM model by 6. 6% relative, as well as other end-to-end architectures by more than 8. 5% relative.
Une nouvelle mesure de la r\'everb\'eration pour pr\'edire les performances a priori de la transcription de la parole (A new reverberation measure to predict a priori ASR performance)
Dans cette {\'e}tude, nous explorons la pr{\'e}diction a priori de la qualit{\'e} de la transcription automatique de la parole dans le cas de la parole r{\'e}verb{\'e}r{\'e}e enregistr{\'e}e avec un seul microphone.
Reconnaissance de phones fond\'ee sur du Transfer Learning pour des enfants apprenants lecteurs en environnement de classe (Transfer Learning based phone recognition on children learning to read, with speech recorded in a classroom environment)
A conditions {\'e}gales, les performances actuelles de la reconnaissance vocale pour enfants sont inf{\'e}rieures {\`a} celles des syst{\`e}mes pour adultes.
\'Etude des facteurs affectant la compr\'ehensibilit\'e de documents multimodaux : une \'etude exp\'erimentale (Factors affecting the comprehensibility of multimodal documents : an experimental study )
La compr{\'e}hensibilit{\'e} de documents audiovisuels peut d{\'e}pendre de facteurs propres {\`a} l{'}auditeur/spectateur (ex.
Analyse de l'effet de la r\'everb\'eration sur la reconnaissance automatique de la parole (Analyzing how reverberation affects Automatic Speech Recognition)
La Reconnaissance Automatique de la Parole (RAP) est moins performante lorsque le signal de parole est de mauvaise qualit{\'e}.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Subjective Evaluation of Comprehensibility in Movie Interactions
Various research works have dealt with the comprehensibility of textual, audio, or audiovisual documents, and showed that factors related to text (e. g. linguistic complexity), sound (e. g. speech intelligibility), image (e. g. presence of visual context), or even to cognition and emotion can play a major role in the ability of humans to understand the semantic and pragmatic contents of a given document.
Deep Neural Networks for Automatic Speech Processing: A Survey from Large Corpora to Limited Data
In that sense we propose an overview of few-shot techniques and perspectives of using such techniques for the focused speech problems in this survey.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Improving Vehicle Re-Identification using CNN Latent Spaces: Metrics Comparison and Track-to-track Extension
We compared T2TP with I2TP using the same CNN models.
Toward a Computational Multidimensional Lexical Similarity Measure for Modeling Word Association Tasks in Psycholinguistics
This paper presents the first results of a multidisciplinary project, the {``}Evolex{''} project, gathering researchers in Psycholinguistics, Neuropsychology, Computer Science, Natural Language Processing and Linguistics.
Influence de la quantit\'e de donn\'ees sur une t\^ache de segmentation de phones fond\'ee sur les r\'eseaux de neurones (Phone-level speech segmentation with neural networks : influence of the amount of data )
Dans cet article, nous d{\'e}crivons une {\'e}tude exp{\'e}rimentale de segmentation de parole en unit{\'e}s acoustiques sous-lexicales (phones) {\`a} l{'}aide de r{\'e}seaux de neurones.
