网络声学模型

3月16日云栖精选夜读：显著超越流行长短时记忆网络，阿里提出DFSMN语音识别声学模型

在语音顶会ICASSP，阿里巴巴语音交互智能团队的poster论文提出一种改进的前馈序列记忆神经网络结构，称之为深层前馈序列记忆神经网络（DFSMN）。研究人员进一步将深层前馈序列记忆神经网络和低帧率（LFR）技术相结合，构建LFR-DFSMN语音识别声学模型。热点热议显著超越流行长短时记忆网络，阿里提出DFSMN语音识别声学模型作者：技术小能手全球最大独立音乐版权商首次进军中国，为...

显著超越流行长短时记忆网络，阿里提出DFSMN语音识别声学模型

在语音顶会ICASSP，阿里巴巴语音交互智能团队的poster论文提出一种改进的前馈序列记忆神经网络结构，称之为深层前馈序列记忆神经网络（DFSMN）。研究人员进一步将深层前馈序列记忆神经网络和低帧率（LFR）技术相结合，构建LFR-DFSMN语音识别声学模型。该模型在大词汇量的英文识别和中文识别任务上都可以取得相比于目前最流行的基于长短时记忆单元的双向循环神经网络（BLSTM）的识别系统显著...

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