Patent Document ID: 9153231
Application ID: 13836141

Base Claim:
1. A method of updating speech recognition neural networks, the method comprising: receiving a first audio signal comprising a first speech utterance; performing speech recognition on the first audio signal based at least in part on an acoustic model neural network to obtain a lattice of speech recognition results, wherein the lattice comprises a first path associated with a first score a second path associate with a second score; updating first weights of the acoustic model neural network substantially in real time, wherein updating the first weights comprises performing a first update using information associated with the first path and performing a second update using information associated with the second path; receiving a second audio signal comprising a second speech utterance; and performing speech recognition on the second audio signal based at least in part on the acoustic model neural network and the updated first weights.

---

Claim 3:
3. The method of claim 1 , further comprising: computing a feature vector from the first audio signal; determining a hidden Markov model state associated with the feature vector from the first path of the lattice of speech recognition results; and wherein updating the first weights of the acoustic model neural network comprises using the feature vector as an input to the acoustic model neural network and the hidden Markov model state as an output to the acoustic model neural network.