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Audio language models fail to fully utilize encoded speaking style

By PulseAugur Editorial · [1 sources] ·

A new research paper titled "Heard but Not Heeded: Paralinguistic Information Encoding and Loss in Audio-Language Models" analyzes how four open-source audio language models—Whisper-large-v2, Qwen2-Audio-7B Instruct, Qwen2.5-Omni-7B, and Chroma-4B—encode and utilize paralinguistic information, such as speaking style. The study, utilizing the Expresso dataset, found that while these models strongly encode speaking style in their later encoder layers, this information is significantly degraded before reaching the final output. The research highlights a discrepancy between the information encoded by the models and what they ultimately use, indicating a limitation in current audio language model capabilities. AI

IMPACT Highlights a key limitation in current audio language models regarding the use of paralinguistic information, potentially guiding future research and development.

RANK_REASON The cluster contains an academic paper detailing research findings on audio language models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Audio language models fail to fully utilize encoded speaking style

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The cluster contains an academic paper detailing research findings on audio language models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Bhuvan Koduru, Dareen Safar B Alharthi, Rita Singh, Bhiksha Raj ·

    Heard but Not Heeded: Paralinguistic Information Encoding and Loss in Audio-Language Models

    arXiv:2609.00727v1 Announce Type: cross Abstract: Audio language models are designed to understand speech, yet it remains unclear whether they capture how something is said beyond what is said. We present a mechanistic analysis of paralinguistic information in four open source mo…

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