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English(EN) ufakzeka-kulak: Building and Evaluating a 31.6M-Parameter Turkish Speech Recognizer from Scratch

发布新的开源土耳其语语音识别模型

研究人员开发了“ufakzeka-kulak”,一个拥有3160万参数的新型开源土耳其语语音识别模型。该模型采用了FastConformer编码器,结合了令牌和持续时间换能器(TDT)以及CTC头。在近5000小时的授权数据上训练后,在特定的土耳其语测试集上,其词错误率(WER)与Whisper base和small模型相比具有竞争力,甚至在某些情况下更低,但不及Whisper large-v3。 AI

影响 为土耳其语语音识别提供了一个新的开源选项,有可能提高土耳其语应用程序的可访问性和性能。

排序理由 新开源模型及其在研究论文中的评估发布。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

发布新的开源土耳其语语音识别模型

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新开源模型及其在研究论文中的评估发布。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Sait Furkan Teke (ufak AI) ·

    ufakzeka-kulak:从零开始构建和评估一个拥有3160万参数的土耳其语语音识别器

    arXiv:2611.03605v1 Announce Type: new Abstract: ufakzeka-kulak is an open Turkish speech-to-text model of 31.6M parameters, a FastConformer encoder with a token-and-duration transducer (TDT) and a CTC head, trained from scratch and released under Apache-2.0. It writes cased, punc…