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Mamba architecture shows promise for multilingual ASR in South African languages

By PulseAugur Editorial · [2 sources] ·

Researchers have evaluated the Mamba architecture for automatic speech recognition (ASR) in seven South African languages, comparing its performance to a Conformer baseline. Mamba demonstrated comparable accuracy to Conformer while requiring fewer computational resources and training faster. Multilingual training with Mamba improved performance over monolingual approaches, though explicit language information did not enhance in-domain accuracy but did boost cross-corpus robustness. Ablation studies in low-resource settings showed that language embeddings were beneficial, acting as task-specific control vectors rather than capturing linguistic similarity. AI

IMPACT Mamba shows potential for efficient and effective multilingual ASR, particularly in under-resourced language contexts.

RANK_REASON Academic paper detailing model evaluation on specific languages and tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Mamba architecture shows promise for multilingual ASR in South African languages

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Academic paper detailing model evaluation on specific languages and tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Jesujoba O. Alabi, Julian Herreilers, Badr M. Abdullah, Dietrich Klakow ·

    From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages

    arXiv:2607.01502v1 Announce Type: new Abstract: Recent advances in automatic speech recognition (ASR) have explored different sequence models, including Conformer-based models and newer state space models such as Mamba. Although prior work has evaluated these architectures in mul…

  2. arXiv cs.CL TIER_1 English(EN) · Dietrich Klakow ·

    From Monolingual to Multilingual: Evaluating Mamba for ASR in South African Languages

    Recent advances in automatic speech recognition (ASR) have explored different sequence models, including Conformer-based models and newer state space models such as Mamba. Although prior work has evaluated these architectures in multiple languages, their effectiveness in African …

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