Search Results for author:
Found 17 papers, 7 papers with code
Findings of the IWSLT 2022 Evaluation Campaign
The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.
Multilingual DistilWhisper: Efficient Distillation of Multi-task Speech Models via Language-Specific Experts
Whisper is a multitask and multilingual speech model covering 99 languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
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.
NAVER LABS Europe's Multilingual Speech Translation Systems for the IWSLT 2023 Low-Resource Track
This paper presents NAVER LABS Europe's systems for Tamasheq-French and Quechua-Spanish speech translation in the IWSLT 2023 Low-Resource track.
ON-TRAC Consortium Systems for the IWSLT 2022 Dialect and Low-resource Speech Translation Tasks
This paper describes the ON-TRAC Consortium translation systems developed for two challenge tracks featured in the Evaluation Campaign of IWSLT 2022: low-resource and dialect speech translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
A Study of Gender Impact in Self-supervised Models for Speech-to-Text Systems
These models are pre-trained on unlabeled audio data and then used in speech processing downstream tasks such as automatic speech recognition (ASR) or speech translation (ST).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Speech Resources in the Tamasheq Language
In this paper we present two datasets for Tamasheq, a developing language mainly spoken in Mali and Niger.
Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
Our results suggest that neural models for speech discretization are difficult to exploit in our setting, and that it might be necessary to adapt them to limit sequence length.
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
Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
For answering this question, we use the MaSS multilingual speech corpus (Boito et al., 2020) for creating 56 bilingual pairs that we apply to the task of low-resource unsupervised word segmentation and alignment.
ON-TRAC Consortium End-to-End Speech Translation Systems for the IWSLT 2019 Shared Task
This paper describes the ON-TRAC Consortium translation systems developed for the end-to-end model task of IWSLT Evaluation 2019 for the English-to-Portuguese language pair.
How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages
For language documentation initiatives, transcription is an expensive resource: one minute of audio is estimated to take one hour and a half on average of a linguist's work (Austin and Sallabank, 2013).
MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible
However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date. Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8, 130 parallel spoken utterances across 8 languages (56 language pairs).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
This task consists in aligning word sequences in a source language with phoneme sequences in a target language, inferring from it word segmentation on the target side [5].
A small Griko-Italian speech translation corpus
This paper presents an extension to a very low-resource parallel corpus collected in an endangered language, Griko, making it useful for computational research.
Unwritten Languages Demand Attention Too! Word Discovery with Encoder-Decoder Models
Word discovery is the task of extracting words from unsegmented text.
