Does Your Voice Assistant Remember? Analyzing Conversational Context Recall and Utilization in Voice Interaction Models
Recent advancements in multi-turn voice interaction models have improved user-model communication.However, while closed-source models effectively retain and recall past utterances, whether open-source models share this ability remains unexplored.To fill this gap, we systematically evaluate how well open-source interaction models utilize past utterances using ContextDialog, a benchmark we proposed for this purpose.Our findings show that speechbased models have more difficulty than textbased ones, especially when recalling information conveyed in speech, and even with retrieval-augmented generation, models still struggle with questions about past utterances.These insights highlight key limitations in opensource models and suggest ways to improve memory retention and retrieval robustness.
Authors
- Nohil Park
- Heeseung Kim
- Sungroh Yoon
- Sangkwon Park
- Jiheum Yeom
- Shyr-Shen Yu (ORCID: https://orcid.org/0000-0001-5711-5018)
- Che Hyun Lee
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.18653/v1/2025.findings-acl.470
- Primary Topic
- Speech and dialogue systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Research Foundation
- Seoul National University
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea
- Samsung
- Institute for Information and Communications Technology Promotion