You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: We use an architecture with 8 hidden layers each containing 2560 rectified linear units and a final softmax layer with14,000 labels (HMM targets h_{t}). The input is 26 frames of 40 Mel-scaled filterbank coefficients with a 10ms advanceper frame and we predict the HMM state of 21{}^{st} frame. The total number of parameters is about 85M. This is aslightly outdated version of the acoustic model used by Android voice search, and should be considered as a very strongbaseline. To train the DNN acoustic model we use about 2000 hours of spoken English data, which yields about 700Mtraining examples. This system achieves a frame accuracy of 58.9%, and a Word Error Rate (WER) of 10.9% on our development set.

Question: For the speech recognition task, based on the information provided by the authors on the total number of samples in the dataset, how long (in seconds) is each training sample?
P0: According to the authors, they used about 2000 hours of spoken English data which yielded about 700M training examples. Approximately, the length of the average training sample would be 0.01 seconds. The specific length of each training sample cannot be answered from this paper.