Multilingual and Cross-cultural interactions for context-aware, and bias-controlled dialogue systems for safety-critical applications

Informacje na temat projektu

ELOQUENCE

Identyfikator umowy o grant: 101135916

DOI

10.3030/101135916

Data podpisania przez KE 29 Listopada 2023

Data rozpoczęcia 1 Stycznia 2024

Data zakończenia 31 Grudnia 2026

Finansowanie w ramach

• Digital, Industry and Space

Koszt całkowity

€ 5 072 543,75

Wkład UE

€ 5 072 543,75

Koordynowany przez

TELEFONICA INNOVACION DIGITAL SL
Spain

CORDIS oferuje możliwość skorzystania z odnośników do publicznie dostępnych publikacji i rezultatów projektów realizowanych w ramach programów ramowych HORYZONT.

Odnośniki do rezultatów i publikacji związanych z poszczególnymi projektami 7PR, a także odnośniki do niektórych konkretnych kategorii wyników, takich jak zbiory danych i oprogramowanie, są dynamicznie pobierane z systemu OpenAIRE .

Rezultaty

Documents, reports (12)

Emerging ELOQUENCE technology- approved by the ELOQUENCE Community

Finalized at TLR=3 stage, this report assesses emerging ELOQUENCE outputs as being respectful of EU values, with particular emphasis on gender, cultural or racial biases.

Dissemination, Communication and Exploitation Plan

Overall DEC plan, with KPIs and benchmarks, and campaign planning. Also includes the website.

Ethics Compliance Management Report

The Ethics requirements and compliance methodology for responsible research.

Algorithms definition, baselines, open issues and use cases

Methodologies applied for both knowledge-based approaches and semi-supervised learning, and applicability to use cases.

Retrieval model for conversational style queries

The methodologies of integrating conversational LLM with FIR subsystem, discussion of open research questions in the context of ELOQUENCE. Codebase implementing the FIR, evaluation of the FIR precision given conversational queries.

Dissemination, Communication and Exploitation Plan II

Overall DEC plan, with KPIs and benchmarks, and campaign planning. Also includes the website.

Conversational LLM

Methodologies for LLM finetuning and simulation/ augmentation of conversational training data, and applicability to use cases. Comparison with SOTA models. Codebase implementing the fine-tuning on selected datasets.

Report on linguistic expression respectful of EU values

Report on requirements for machine-generated verbal communication respectful of European values as enshrined in Article 2 of the EU Treaty.

Pilot Requirements & Usability Evaluation

Uses cases, requirements and outcomes for the different pilots. Summary of the set of KPIs, criteria and methodology to evaluate the ELOQUENCE usability.

Open source datasets suitable for semi-structured, unstructured and multi-turn conversations

Requirements for semi-structured, multi-turn and unstructured dialogues, available/relevant literature review on evaluation of dialogues and description of methodology on how the fused datasets are generated

Project Management Handbook

Management procedure, consortium communication tools and the quality and risk management plans.

Methodology for jointly training FIR and response generator

The methodologies on interconnecting FIR and response generator, analysis of scenarios relevant to ELOQUENCE. Implementation of the FIR and response generator joint training.

Data Management Plan (2)

ELOQUENCE DMP

The legal aspects and the data management plan for the collection and processing of data throughout the project activities.

ELOQUENCE DMP II

The legal aspects and the data management plan for the collection and processing of data throughout the project activities.

Demonstrators, pilots, prototypes (1)

ELOQUENCE Interactive Playground

Initial version of the Interactive Playground for the LM validation.

Publikacje

Conference proceedings (13)

Comparing Data Augmentation Methods for End-to-End Task-Oriented Dialog Systems

Autorzy: Christos Vlachos, Themos Stafylakis, Ion Androutsopoulos
Opublikowane w: Findings of the Association for Computational Linguistics ACL 2024, 2024
Wydawca: Association for Computational Linguistics
DOI: 10.18653/V1/2024.FINDINGS-ACL.431

BESST Dataset: A Multimodal Resource for Speech-based Stress Detection and Analysis

Autorzy: Jan Pešán, Vojtěch Juřík, Martin Karafiát, Jan Černocký
Opublikowane w: Interspeech 2024, 2024
Wydawca: ISCA
DOI: 10.21437/INTERSPEECH.2024-42

BUT systems and analyses for the ASVspoof 5 Challenge

Autorzy: Johan Rohdin, Lin Zhang, Plchot Oldřich, Vojtěch Staněk, David Mihola, Junyi Peng, Themos Stafylakis, Dmitriy Beveraki, Anna Silnova, Jan Brukner, Lukáš Burget
Opublikowane w: The Automatic Speaker Verification Spoofing Countermeasures Workshop (ASVspoof 2024), 2024
Wydawca: ISCA
DOI: 10.21437/ASVSPOOF.2024-4

TokenVerse: Towards Unifying Speech and NLP Tasks via Transducer-based ASR

Autorzy: Shashi Kumar, Srikanth Madikeri, Juan Pablo Zuluaga Gomez, Iuliia Thorbecke, Esaú Villatoro-tello, Sergio Burdisso, Petr Motlicek, Karthik Pandia D S, Aravind Ganapathiraju
Opublikowane w: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Wydawca: Association for Computational Linguistics
DOI: 10.18653/V1/2024.EMNLP-MAIN.1167

Pretraining End-to-End Keyword Search with Automatically Discovered Acoustic Units

Autorzy: Bolaji Yusuf, Jan Honza Cernocky, Murat Saraçlar
Opublikowane w: Interspeech 2024, 2024
Wydawca: ISCA
DOI: 10.21437/INTERSPEECH.2024-1713

Parameter-Efficient Transfer Learning of Audio Spectrogram Transformers

Autorzy: Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti, Mirco Ravanelli
Opublikowane w: 2024 IEEE 34th International Workshop on Machine Learning for Signal Processing (MLSP), 2024
Wydawca: IEEE
DOI: 10.1109/MLSP58920.2024.10734776

Multitask Speech Recognition and Speaker Change Detection for Unknown Number of Speakers

Autorzy: Shashi Kumar, Srikanth Madikeri, Iuliia Nigmatulina, Esaú Villatoro-Tello, Petr Motlicek, Karthik Pandia, S. Pavankumar Dubagunta, Aravind Ganapathiraju
Opublikowane w: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
Wydawca: IEEE
DOI: 10.1109/ICASSP48485.2024.10446130

Large Language Models are Strong Audio-Visual Speech Recognition Learners

Autorzy: Umberto Cappellazzo, Minsu Kim, Honglie Chen, Pingchuan Ma, Stavros Petridis, Daniele Falavigna, Alessio Brutti, Maja Pantic
Opublikowane w: ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
Wydawca: IEEE
DOI: 10.1109/ICASSP49660.2025.10889251

Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction

Autorzy: Sergio Burdisso, Srikanth Madikeri, Petr Motlicek
Opublikowane w: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024
Wydawca: Association for Computational Linguistics
DOI: 10.18653/V1/2024.EMNLP-MAIN.310

Multimodal Emotion Recognition Using Compressed Graph Neural Networks

Autorzy: Tijana Đurkić, Nikola Simić, Siniša Suzić, Dragana Bajović, Zoran Perić, Vlado Delić
Opublikowane w: Lecture Notes in Computer Science, Speech and Computer, 2025
Wydawca: Springer Nature Switzerland
DOI: 10.1007/978-3-031-78014-1_9

BUT/JHU System Description for CHiME-8 NOTSOFAR-1 Challenge

Autorzy: Alexander Polok, Dominik Klement, Jiangyu Han, Šimon Sedláček, Bolaji Yusuf, Matthew Maciejewski, Matthew S Wiesner, Lukáš Burget
Opublikowane w: 8th International Workshop on Speech Processing in Everyday Environments (CHiME 2024), 2024
Wydawca: ISCA
DOI: 10.21437/CHIME.2024-4

Efficient Fine-tuning of Audio Spectrogram Transformers via Soft Mixture of Adapters

Autorzy: Umberto Cappellazzo, Daniele Falavigna, Alessio Brutti
Opublikowane w: Interspeech 2024, 2024
Wydawca: ISCA
DOI: 10.21437/INTERSPEECH.2024-38

MT-LENS: An all-in-one Toolkit for Better Machine Translation Evaluation

Autorzy: Javier García Gilabert, Carlos Escolano, Audrey Mash, Xixian Liao, Maite Melero
Opublikowane w: Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations), 2025
Wydawca: Association for Computational Linguistics
DOI: 10.18653/V1/2025.NAACL-DEMO.6