“智能硬件-课程阅读1”版本间的差异
来自iCenter Wiki
| 第1行： | 第1行： | ||
===Group1=== | ===Group1=== | ||
| + | Google | ||
Convolutional, long short-term memory, fully connected deep neural networks, ICASSP 2015. | Convolutional, long short-term memory, fully connected deep neural networks, ICASSP 2015. | ||
| 第6行： | 第7行： | ||
===Group2=== | ===Group2=== | ||
| + | |||
| + | Google | ||
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition, ICASSP 2015. | Listen, attend and spell: A neural network for large vocabulary conversational speech recognition, ICASSP 2015. | ||
===Group3=== | ===Group3=== | ||
| + | JHU | ||
Audio augmentation for speech recognition, InterSpeech 2015. | Audio augmentation for speech recognition, InterSpeech 2015. | ||
===Group4=== | ===Group4=== | ||
| + | |||
| + | Baidu | ||
Deep Speech 2 End-to-End Speech Recognition in English and Mandarin, JMLR 2016. | Deep Speech 2 End-to-End Speech Recognition in English and Mandarin, JMLR 2016. | ||
2017年1月13日 (五) 10:02的版本
Group1
Convolutional, long short-term memory, fully connected deep neural networks, ICASSP 2015.
Context dependent phone models for LSTM RNN acoustic modelling, ICASSP 2015.
Group2
Listen, attend and spell: A neural network for large vocabulary conversational speech recognition, ICASSP 2015.
Group3
JHU
Audio augmentation for speech recognition, InterSpeech 2015.
Group4
Baidu
Deep Speech 2 End-to-End Speech Recognition in English and Mandarin, JMLR 2016.
