Post-Doctoral Research Visit F/M Automatic analysis of alignment between speakers in conversations

TN France; Paris; Hybride; EUR 40 000 - 70 000; Plein temps

Résumé du poste

An exciting post-doctoral opportunity awaits in Paris, focusing on the development of socially-aware neural conversational models. This role involves investigating human conversational behaviors and developing methodologies to enhance communication in AI systems. Join a dynamic research team dedicated to advancing the field of Natural Language Processing, where you will engage in innovative projects and collaborate with experts. Enjoy a flexible working environment with generous leave policies and professional development opportunities. If you are passionate about AI and linguistics, this position is perfect for you.

Prestations

Partial reimbursement of public transport costs

7 weeks of annual leave

10 extra days off due to RTT

Possibility of teleworking

Flexible working hours

Professional equipment available

Social, cultural and sports events

Qualifications

• PhD in relevant fields required.
• Strong knowledge of NLP and machine learning techniques.

Responsabilités

• Investigate and analyze miscommunication in human interaction.
• Produce annotated corpus and propose models for identifying miscommunication triggers.

Connaissances

Natural Language Processing

Machine Learning

Conversational AI

Corpus Annotation

Deep Learning

English Fluency

Formation

PhD in Natural Language Processing

PhD in Computational Linguistics

PhD in Computer Science

Description du poste

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Post-Doctoral Research Visit F/M Automatic analysis of alignment between speakers in conversations, Paris

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Client:

INRIA

Location:

Paris, France

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

8fc4a7474f54

Job Views:

1

Posted:

29.04.2025

Expiry Date:

13.06.2025

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Job Description:

This postdoc position is offered in the context of the ANR PRME SINNet project (Socio-Inspired Neural Networks for Conversational Systems), aiming to develop socially-aware neural conversational models which are able to adapt their language and behavior to the agent-user social relationship.

One of the key human behaviors that is desirable for automatic systems to imitate is alignment, also called entrainment, which consists in mirrorring the interlocutor's behavior and language use. This postdoc position will specifically be devoted to the characterization and modeling of alignment at the level of word meaning.

The postdoc will focus on cases of miscommunication due to a lack of lexico-semantic alignment between speakers in a conversation.

The goals will be to:

• Investigate, analyze and characterize this phenomenon in human interaction: how humans produce, signal, and solve misunderstandings or disagreements due to specific lexical elements in dialog;
• Produce a semi-automatically annotated corpus with instances of this phenomenon;
• Propose models that can identify word usages that are potential triggers or causes of miscommunication, as well as pinning down the reason why they may be problematic and for whom;
• Build or adapt systems that are able to both avoid producing potential triggers, adapting to the speaker and the conversational situation; mirror human behavior and repair strategies when faced with such triggers, e.g. asking for disambiguation.
• Provide ways of evaluating the proposed methodology.

The successful postdoc candidate will be part of INRIA's ALMAnaCH team, specialized in NLP. Besides the research tasks mentioned under Assignments, they will be expected to participate and collaborate in the team's activities, including seminars and reading groups.

Skills

• PhD in Natural Language Processing, Computational Linguistics, Computer Science with a specialization in Machine Learning, or related fields;
• Knowledge of deep learning as well as more traditional machine learning techniques;
• Desired prior experience on conversational AI, word meaning representations and corpus annotation;
• Fluency in English.

Avantages

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking
• Flexible organization of working hours(after 12 months of employment)
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities