Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network.

Abstract: Methods, systems, and apparatus for determining resource quality based on resource competition. In an aspect, a method comprises: for each of a plurality of resource locators: generating first value for the resource locator that indicates, for a plurality of first sets of search results that each include the resource locator, a number of occurrences of other resource locators that were impressed and not selected when the resource locator was selected; generating a second value for the resource locator that indicates, for a plurality of second sets of search results that each include the resource locator, a number of occurrences of other resource locators that were selected when the resource locator was impressed and not selected; and generating, based on a difference between the first value and the second value, an adjustment factor for the resource locator for adjusting a score associated with the resource locator during a search operation.

Abstract: Methods, systems, and apparatus for determining resource quality based on resource competition. In an aspect, a method comprises: for each of a plurality of resource locators: generating first value for the resource locator that indicates, for a plurality of first sets of search results that each include the resource locator, a number of occurrences of other resource locators that were impressed and not selected when the resource locator was selected; generating a second value for the resource locator that indicates, for a plurality of second sets of search results that each include the resource locator, a number of occurrences of other resource locators that were selected when the resource locator was impressed and not selected; and generating, based on a difference between the first value and the second value, an adjustment factor for the resource locator for adjusting a score associated with the resource locator during a search operation.