Search Results for author:
Found 16 papers, 3 papers with code
ON-TRAC’ systems for the IWSLT 2021 low-resource speech translation and multilingual speech translation shared tasks
This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2021, low-resource speech translation and multilingual speech translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
The Spoken Language Understanding MEDIA Benchmark Dataset in the Era of Deep Learning: data updates, training and evaluation tools
In this paper, we focus on the French MEDIA SLU dataset, distributed since 2005 and used as a benchmark dataset for a large number of research works.
Impact Analysis of the Use of Speech and Language Models Pretrained by Self-Supersivion for Spoken Language Understanding
Pretrained models through self-supervised learning have been recently introduced for both acoustic and language modeling.
Performance Analysis of Speech Encoders for Low-Resource SLU and ASR in Tunisian Dialect
In contrast to existing research, this paper contributes by comparing the effectiveness of SSL approaches in the context of (i) the low-resource spoken Tunisian Arabic dialect and (ii) its combination with a low-resource SLU and ASR scenario, where only a few semantic annotations are available for fine-tuning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Open-Source Conversational AI with SpeechBrain 1.0
This paper presents SpeechBrain 1. 0, a significant milestone in the evolution of the toolkit, which now has over 200 recipes for speech, audio, and language processing tasks, and more than 100 models available on Hugging Face.
Sonos Voice Control Bias Assessment Dataset: A Methodology for Demographic Bias Assessment in Voice Assistants
Recent works demonstrate that voice assistants do not perform equally well for everyone, but research on demographic robustness of speech technologies is still scarce.
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing.
Federated Learning for ASR based on Wav2vec 2.0
This paper presents a study on the use of federated learning to train an ASR model based on a wav2vec 2. 0 model pre-trained by self supervision.
End-to-end model for named entity recognition from speech without paired training data
Our approach is based on the use of an external model trained to generate a sequence of vectorial representations from text.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
Retrieving Speaker Information from Personalized Acoustic Models for Speech Recognition
The widespread of powerful personal devices capable of collecting voice of their users has opened the opportunity to build speaker adapted speech recognition system (ASR) or to participate to collaborative learning of ASR.
Privacy attacks for automatic speech recognition acoustic models in a federated learning framework
This paper investigates methods to effectively retrieve speaker information from the personalized speaker adapted neural network acoustic models (AMs) in automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Where are we in semantic concept extraction for Spoken Language Understanding?
More recent works on self-supervised training with unlabeled data open new perspectives in term of performance for automatic speech recognition and natural language processing.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
In this paper, we propose LeBenchmark: a reproducible framework for assessing SSL from speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+6
A Multimodal Educational Corpus of Oral Courses: Annotation, Analysis and Case Study
The use cases concern scientific fields from both speech and text processing, with language model adaptation, thematic segmentation and transcription to slide alignment.
Apport de l'adaptation automatique des mod\`eles de langage pour la reconnaissance de la parole: \'evaluation qualitative extrins\`eque dans un contexte de traitement de cours magistraux (Contribution of automatic adaptation of language models for speech recognition : extrinsic qualitative evaluation in a context of educational courses)
Les transcriptions automatiques de ces syst{\`e}mes sont de plus en plus exploitables et utilis{\'e}es dans des syst{\`e}mes complexes de traitement automatique du langage naturel, par exemple pour la traduction automatique, l{'}indexation, la recherche documentaire... Des {\'e}tudes r{\'e}centes ont propos{\'e} des m{\'e}triques permettant de comparer la qualit{\'e} des transcriptions automatiques de diff{\'e}rents syst{\`e}mes en fonction de la t{\^a}che vis{\'e}e. Dans cette {\'e}tude nous souhaitons mesurer, qualitativement, l{'}apport de l{'}adaptation automatique des mod{\`e}les de langage au domaine vis{\'e} par un cours magistral.
Le corpus PASTEL pour le traitement automatique de cours magistraux (PASTEL corpus for automatic processing of lectures)
Cet enrichissement s{'}appuie sur des traitements automatiques du langage naturel effectu{\'e}s sur les transcriptions automatiques.
