Patent Document ID: 9799327
Application ID: 15055476

Base Claim:
1. A computer implemented method comprising: obtaining an input acoustic sequence, the input acoustic sequence representing an utterance, and the input acoustic sequence comprising a respective acoustic feature representation at each of a first number of time steps; processing the input acoustic sequence using a first neural network to convert the input acoustic sequence into an alternative representation for the input acoustic sequence, wherein the alternative representation for the input acoustic sequence comprises a respective alternative acoustic feature representation for each of a second number of time steps, and wherein the second number is smaller than the first number; processing the alternative representation for the input acoustic sequence using an attention-based Recurrent Neural Network (RNN) to generate, for each position in an output sequence order, a set of substring scores that includes a respective substring score for each substring in a set of substrings; and generating a sequence of substrings that represent a transcription of the utterance.

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Claim 8:
8. The method of claim 1 , wherein processing the alternative representation for the input acoustic sequence using an attention-based RNN comprises, for an initial position in the output sequence order: processing a placeholder start of sequence token and a placeholder initial attention context vector using the attention-based RNN to update a hidden state of the attention-based RNN from an initial hidden state to a hidden state for the initial position in the output sequence order; generating an attention context vector for the initial position from the alternative representation and the RNN hidden state for the initial position in the output sequence order; and generating the set of substring scores for the initial position using the attention context vector for the initial position and the RNN hidden state for the initial position.