I am reading this paper: skype translator where they use CD-DNN-HMMs (Context dependent Deep neural Networks with Hidden Markov Models). I can understand the idea of the project and the architecture they've designed but I don't get what are the senones. I have been looking for a definition but I haven't found anything
—We propose a novel context-dependent (CD) model for large-vocabulary speech recognition (LVSR) that leverages recent advances in using deep belief networks for phone recognition. We describe a pre-trained deep neural network hidden Markov model (DNN-HMM) hybrid architecture that trains the DNN to produce a distribution over senones (tied triphone states) as its output
Please if you could give me an explanation about this I would really appreciate it.
I've found this definition in this paper:
We propose to model subphonetic events with Markov states and treat the state in phonetic hidden Markov models as our basic subphonetic unit -- senone. A word model is a concatenation of state-dependent senones and senones can be shared across different word models.
I guess they are used in the Hidden Markov Model part of the architecture in the first paper. Are they the states of the HMM? The outputs of the DNN?