Habibi: Laying the Open-Source Foundation of Unified-Dialectal Arabic Speech Synthesis

• URL: http://arxiv.org/abs/2601.13802v1
• Date: Tue, 20 Jan 2026 10:02:11 GMT
• Title: Habibi: Laying the Open-Source Foundation of Unified-Dialectal Arabic Speech Synthesis
• Authors: Yushen Chen, Junzhe Liu, Yujie Tu, Zhikang Niu, Yuzhe Liang, Kai Yu, Chunyu Qiang, Chen Zhang, Xie Chen,
• Abstract summary: We present Habibi, a suite of specialized and unified text-to-speech models.<n>Our approach outperforms the leading commercial service in generation quality.<n>We create the first systematic benchmark for multi-dialect Arabic speech synthesis.
• Score: 20.50741854108831
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A notable gap persists in speech synthesis research and development for Arabic dialects, particularly from a unified modeling perspective. Despite its high practical value, the inherent linguistic complexity of Arabic dialects, further compounded by a lack of standardized data, benchmarks, and evaluation guidelines, steers researchers toward safer ground. To bridge this divide, we present Habibi, a suite of specialized and unified text-to-speech models that harnesses existing open-source ASR corpora to support a wide range of high- to low-resource Arabic dialects through linguistically-informed curriculum learning. Our approach outperforms the leading commercial service in generation quality, while maintaining extensibility through effective in-context learning, without requiring text diacritization. We are committed to open-sourcing the model, along with creating the first systematic benchmark for multi-dialect Arabic speech synthesis. Furthermore, by identifying the key challenges in and establishing evaluation standards for the process, we aim to provide a solid groundwork for subsequent research. Resources at https://SWivid.github.io/Habibi/ .

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