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Found 9 papers, 2 papers with code
Qwant Research @DEFT 2019 : appariement de documents et extraction d'informations \`a partir de cas cliniques (Document matching and information retrieval using clinical cases)
Pour r{\'e}soudre cette t{\^a}che, nous proposons une approche reposant sur des mod{\`e}les de langue et {\'e}valuons l{'}impact de diff{\'e}rents pr{\'e}-traitements et de diff{\'e}rentes techniques d{'}appariement sur les r{\'e}sultats.
Qwant Research @DEFT 2019: Document matching and information retrieval using clinical cases
For this task, we propose an approach based on language models and evaluate the impact on the results of different preprocessings and matching techniques.
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling
We introduce a new unsupervised task, spoken language modeling: the learning of linguistic representations from raw audio signals without any labels, along with the Zero Resource Speech Benchmark 2021: a suite of 4 black-box, zero-shot metrics probing for the quality of the learned models at 4 linguistic levels: phonetics, lexicon, syntax and semantics.
The Zero Resource Speech Challenge 2021: Spoken language modelling
We present the Zero Resource Speech Challenge 2021, which asks participants to learn a language model directly from audio, without any text or labels.
Probing phoneme, language and speaker information in unsupervised speech representations
Language information, however, is very salient in the bilingual model only, suggesting CPC models learn to discriminate languages when trained on multiple languages.
Is the Language Familiarity Effect gradual? A computational modelling approach
According to the Language Familiarity Effect (LFE), people are better at discriminating between speakers of their native language.
Are word boundaries useful for unsupervised language learning?
However, word boundary information may be absent or unreliable in the case of speech input (word boundaries are not marked explicitly in the speech stream).
ProsAudit, a prosodic benchmark for self-supervised speech models
In the lexical task, the model needs to correctly distinguish between pauses inserted between words and within words.
EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models
We introduce EmphAssess, a prosodic benchmark designed to evaluate the capability of speech-to-speech models to encode and reproduce prosodic emphasis.
