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

新的开源土耳其语语音识别模型ufakzeka-kulak发布

一个名为ufakzeka-kulak的新开源土耳其语语音转文本模型已被开发出来,拥有3160万个参数。该模型采用带有令牌和持续时间换能器(TDT)以及CTC头部的FastConformer编码器,并在近5000小时的许可数据上进行了训练。它能够生成区分大小写、带标点符号的土耳其语文本,并将数字写成单词。评估显示,与Whisper等模型相比,该模型在FLEURS土耳其语测试集上达到了0.0921的词错误率,表现具有竞争力。 AI

影响 为土耳其语语音识别提供了一个新的开源选项,有望提高该语言的可访问性和研究水平。

排序理由 发布了一个具有性能基准的新开源模型。[lever_c_demoted from research: ic=1 ai=1.0]

在 Hugging Face Daily Papers 阅读 →

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

新的开源土耳其语语音识别模型ufakzeka-kulak发布

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发布了一个具有性能基准的新开源模型。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    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

    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, punctuated Turkish with numbers as words. Its 4,977 …