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Research PaperResearchia:202609.25058

Do Audio Language Models Hear and Read Distinctive Features Alike?

Yuanhao Chen

Abstract

Audio language models pass speech and text through a single decoder. We ask whether that decoder represents a distinctive feature in the same direction when a phoneme is heard and when it is read. For minimal pairs of phonemes differing in one feature, we take the offset between the two members' mean representations. Averaging those offsets gives a direction for each stream, and we measure the cosine between the two. Because the two streams already agree about arbitrary phoneme pairs, we compare...

Submitted: September 25, 2026Subjects: Machine Learning; Data Science

Description / Details

Audio language models pass speech and text through a single decoder. We ask whether that decoder represents a distinctive feature in the same direction when a phoneme is heard and when it is read. For minimal pairs of phonemes differing in one feature, we take the offset between the two members' mean representations. Averaging those offsets gives a direction for each stream, and we measure the cosine between the two. Because the two streams already agree about arbitrary phoneme pairs, we compare every measure against a reference built from random pairings rather than against zero. We apply this to 6 models, 7 features and 15 languages from 11 families. Only voicing in the two Qwen2.5-Omni models exceeds that reference after correction for multiple testing, and the reference varies by a factor of seven between models. In three of the six models, voicing has one direction in audio across the 14 languages with enough minimal pairs to measure it, and every language pair agrees in two of them. The model family, not the model size, predicts which stream represents a feature.


Source: arXiv:2609.30167v1 - http://arxiv.org/abs/2609.30167v1 PDF: https://arxiv.org/pdf/2609.30167v1 Original Link: http://arxiv.org/abs/2609.30167v1

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Submission Info
Date:
Sep 25, 2026
Topic:
Data Science
Area:
Machine Learning
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