Sommelier: Scalable Open Multi-turn Audio Pre-processing for Full-duplex Speech Language Models
As the paradigm of AI shifts from text-based LLMs to Speech Language Models (SLMs), there is a growing demand for full-duplex systems capable of real-time, natural human-computer interaction. However, the development of such models is constrained by the scarcity of high-quality, multi-speaker conversational data, as existing large-scale resources are predominantly single-speaker or limited in volume. Addressing the complex dynamics of natural dialogue, such as overlapping and back-channeling remains a challenge, with standard processing pipelines suffering from diarization errors and ASR hallucinations. To bridge this gap, we present a robust and scalable open-source data processing pipeline designed for full-duplex model.
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Kyudan Jung
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2026-03-30T08:37:48.637Z
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Kyudan Jung
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Jihwan Kim
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2026-04-02T08:17:44.504Z
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Jihwan Kim
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Soyoon Kim
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Jeongoon Kim
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2026-04-01T08:36:17.383Z
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Jeonghoon Kim
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Jaegul Choo
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2026-03-30T10:23:14.262Z
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Jaegul Choo
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Cheonbok Park
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2026-03-30T10:22:53.624Z
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Cheonbok Park
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Sommelier: Scalable Open Multi-turn Audio Pre-processing for Full-duplex Speech Language Models
As the paradigm of AI shifts from text-based LLMs to Speech Language Models (SLMs), there is a growing demand for full-duplex systems capable of real-time, natural human-computer interaction. However, the development of such models is constrained by the scarcity of high-quality, multi-speaker conversational data, as existing large-scale resources are predominantly single-speaker or limited in volume. Addressing the complex dynamics of natural dialogue, such as overlapping and back-channeling remains a challenge, with standard processing pipelines suffering from diarization errors and ASR hallucinations. To bridge this gap, we present a robust and scalable open-source data processing pipeline designed for full-duplex model.
Full-duplex speech language models require high-quality multi-speaker conversational data, which is scarce, necessitating a robust open-source data processing pipeline to address challenges in natural dialogue dynamics and system accuracy.
Speech Language Models full-duplex systems real-time interaction multi-speaker conversational data diarization errors ASR hallucinations open-source data processing pipeline