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arXiv · 2508.15316

CUPE: Contextless Universal Phoneme Encoder for Language-Agnostic Speech Processing

Abdul Rehman·Jian-Jun Zhang·Xiaosong Yang
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Abstract

Universal phoneme recognition typically requires analyzing long speech segments and language-specific patterns. Many speech processing tasks require pure phoneme representations free from contextual influence, which motivated our development of CUPE - a lightweight model that captures key phoneme features in just 120 milliseconds, about one phoneme's length. CUPE processes short, fixed-width windows independently and, despite fewer parameters than current approaches, achieves competitive cross-lingual performance by learning fundamental acoustic patterns common to all languages. Our extensive evaluation through supervised and self-supervised training on diverse languages, including zero-shot tests on the UCLA Phonetic Corpus, demonstrates strong cross-lingual generalization and reveals that effective universal speech processing is possible through modeling basic acoustic patterns within phoneme-length windows.

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Abdul Rehman, Jian-Jun Zhang, Xiaosong Yang. 2025-08-21. CUPE: Contextless Universal Phoneme Encoder for Language-Agnostic Speech Processing. https://arxiv.org/abs/2508.15316

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