语音识别及其应用出现“井喷式”发展

        在2009-2011年期间。全球语音识别技术普遍转向“深度神经网络”（DNN）平台，DNN架构的层面数量及规模大幅度提升。研究成果频出。出现了“井喷式”发展态势。详细表如今下面8个方面：

1. Scaling up/out and speedup DNN training and decoding;

2. Sequence discriminative training of DNNs;

3. Feature processing by deep models with solid understanding of the underlying mechanisms;

4. Adaptation of DNNs and of related deep models;

5. Multi-task and transfer learning by DNNs and related deep models;

6. Convolution neural networks and how to design them to best exploit domain knowledge of speech;

7. Recurrent neural network and its rich LSTM variants;

8. Other types of deep models including tensor-based models and integrated deep generative/discriminative models.

尤其是近年来，语音识别（SR）技术在社会大众医疗保健、第二外语高效培训、军事航空指挥训练等诸多方面获得成功应用，效果明显。深度神经网络（DNN）技术的详细应用方式是不难想象的。无需多说。

百度李彦宏“中国大脑”提案就是在这样的“井喷式发展”的大背景下提出的。

袁萌 7月15日