Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing spoken query terms. In one aspect, a method includes performing speech recognition on an audio signal to select two or more textual, candidate transcriptions that match a spoken query term, and to establish a speech recognition confidence value for each candidate transcription, obtaining a search history for a user who spoke the spoken query term, where the search history references one or more past search queries that have been submitted by the user, generating one or more n-grams from each candidate transcription, where each n-gram is a subsequence of n phonemes, syllables, letters, characters, words or terms from a respective candidate transcription, and determining, for each n-gram, a frequency with which the n-gram occurs in the past search queries, and a weighting value that is based on the respective frequency.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for adjusting language models. In one aspect, a method includes accessing audio data. Information that indicates a first context is accessed, the first context being associated with the audio data. At least one term is accessed. Information that indicates a second context is accessed, the second context being associated with the term. A similarity score is determined that indicates a degree of similarity between the second context and the first context. A language model is adjusted based on the accessed term and the determined similarity score to generate an adjusted language model. Speech recognition is performed on the audio data using the adjusted language model to select one or more candidate transcriptions for a portion of the audio data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing spoken query terms. In one aspect, a method includes performing speech recognition on an audio signal to select two or more textual, candidate transcriptions that match a spoken query term, and to establish a speech recognition confidence value for each candidate transcription, obtaining a search history for a user who spoke the spoken query term, where the search history references one or more past search queries that have been submitted by the user, generating one or more n-grams from each candidate transcription, where each n-gram is a subsequence of n phonemes, syllables, letters, characters, words or terms from a respective candidate transcription, and determining, for each n-gram, a frequency with which the n-gram occurs in the past search queries, and a weighting value that is based on the respective frequency.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for adjusting language models. In one aspect, a method includes accessing audio data. Information that indicates a first context is accessed, the first context being associated with the audio data. At least one term is accessed. Information that indicates a second context is accessed, the second context being associated with the term. A similarity score is determined that indicates a degree of similarity between the second context and the first context. A language model is adjusted based on the accessed term and the determined similarity score to generate an adjusted language model. Speech recognition is performed on the audio data using the adjusted language model to select one or more candidate transcriptions for a portion of the audio data.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for adjusting language models. In one aspect, a method includes accessing audio data. Information that indicates a first context is accessed, the first context being associated with the audio data. At least one term is accessed. Information that indicates a second context is accessed, the second context being associated with the term. A similarity score is determined that indicates a degree of similarity between the second context and the first context. A language model is adjusted based on the accessed term and the determined similarity score to generate an adjusted language model. Speech recognition is performed on the audio data using the adjusted language model to select one or more candidate transcriptions for a portion of the audio data.

Abstract: The present disclosure includes processing a signal to generate a first sub-set of data, transmitting the first sub-set of data for generation of a reconstructed audio signal, the reconstructed audio signal having a fidelity relative to the signal, processing the signal to generate a second sub-set of data and a third sub-set of data, the second sub-set of data defining a second portion of the signal and comprising data that is different than data of the first sub-set of data, and the third sub-set of data defining a third portion of the signal and comprising data that is different than data of the first and second sub-sets of data, comparing a priority of the second sub-set of data to a priority of the third sub-set of data, and transmitting one of the second sub-set of data and the third sub-set of data over the network for improving the fidelity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for disambiguating contact information. A method includes receiving an audio signal, generating an affinity score based on a frequency with which a user has previously communicated with a contact associated with an item of contact information, and further based on a recency of one or more past interactions between the user and the contact associated with the item of contact information, inferring a probability that the user intends to initiate a communication using the item of contact information based on the affinity score generated for the item of contact information, and generating a communication initiation grammar.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for disambiguating contact information are described. A method includes determining, for each of multiple communications that were initiated by a user of a mobile device, a time when the communication was initiated or received; determining, for each of multiple contacts associated with the user, a probability associated with the contact based at least on the times when the communications were initiated or received; weighting a contact disambiguation grammar according to the probabilities; and processing audio data using the contact disambiguation grammar to select a particular contact.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, identifying a set of geotagged audio signals that correspond to environmental audio associated with the geographic location, weighting each geotagged audio signal of the set of geotagged audio signals based on metadata associated with the respective geotagged audio signal, and using the set of weighted geotagged audio signals to perform noise compensation on the audio signal that corresponds to the utterance.

Abstract: An audio signal generated by a device based on audio input from a user may be received. The audio signal may include at least a user audio portion that corresponds to one or more user utterances recorded by the device. A user speech model associated with the user may be accessed and a determination may be made background audio in the audio signal is below a defined threshold. In response to determining that the background audio in the audio signal is below the defined threshold, the accessed user speech model may be adapted based on the audio signal to generate an adapted user speech model that models speech characteristics of the user. Noise compensation may be performed on the received audio signal using the adapted user speech model to generate a filtered audio signal with reduced background audio compared to the received audio signal.

Abstract: For multiple times in a time period, multiple data points can be received from an accelerometer and from a magnetometer that are included in a mobile computing device. For each of the data points, an orientation and a position of the mobile computing device can be determined based on an acceleration output and a magnetometer output that corresponds to the particular time. A trajectory is determined that represents movement of the mobile computing device during the time period based on the determined orientations and positions of the mobile computing device at the multiple times. Information that characterizes the trajectory is compared to stored information that characterizes a set of one or more base trajectories. Based on the comparison, an operation of the mobile computing device is identified that is associated with a trajectory included in the set of one or more base trajectories.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, adapting one or more acoustic models for the geographic location, and performing speech recognition on the audio signal using the one or more acoustic models model that are adapted for the geographic location.

Abstract: A computer-implemented method for determining content to be displayed includes determining a first size aspect of first content that is to be presented in a graphical user interface. The method includes obtaining second content and causing the second content to be presented in the graphical user interface with the first content, wherein the second content has a second size aspect with a predefined relationship to the first size aspect. A system includes a size determining module determining a first size aspect of first content that is to be presented in a graphical user interface. The system includes a content module obtaining second content based on the first size aspect, the second content having a second size aspect with a predefined relationship to the first size aspect. The system includes a page generating module causing the second content to be presented in the graphical user interface with the first content.

Abstract: This disclosure generally relates to assigning and simultaneously running multiple client-side experiments on client devices. A file includes information regarding experiments that are available, including information regarding “layers,” which are logical, imaginary containers in which each experiment “resides.” Each experiment is associated with one layer. For each experiment, the file includes information regarding a location and size of the experiment within the layer. When the client device takes an action, a software module identifies a value of an identifier associated with the action. Each such identifier is associated with one or more of the layers. The software module can calculate, for each of the associated layers, a location within the layer based on the identifier value. The computer software module can identify, based on the information in the file, each experiment that overlaps with the calculated location within each layer and cause each identified experiment to be activated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, identifying a set of geotagged audio signals that correspond to environmental audio associated with the geographic location, weighting each geotagged audio signal of the set of geotagged audio signals based on metadata associated with the respective geotagged audio signal, and using the set of weighted geotagged audio signals to perform noise compensation on the audio signal that corresponds to the utterance.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing spoken query terms. In one aspect, a method includes performing speech recognition on an audio signal to select two or more textual, candidate transcriptions that match a spoken query term, and to establish a speech recognition confidence value for each candidate transcription, obtaining a search history for a user who spoke the spoken query term, where the search history references one or more past search queries that have been submitted by the user, generating one or more n-grams from each candidate transcription, where each n-gram is a subsequence of n phonemes, syllables, letters, characters, words or terms from a respective candidate transcription, and determining, for each n-gram, a frequency with which the n-gram occurs in the past search queries, and a weighting value that is based on the respective frequency.

Abstract: The present disclosure includes processing a signal to generate a first sub-set of data, transmitting the first sub-set of data for generation of a reconstructed audio signal, the reconstructed audio signal having a fidelity relative to the signal, processing the signal to generate a second sub-set of data and a third sub-set of data, the second sub-set of data defining a second portion of the signal and comprising data that is different than data of the first sub-set of data, and the third sub-set of data defining a third portion of the signal and comprising data that is different than data of the first and second sub-sets of data, comparing a priority of the second sub-set of data to a priority of the third sub-set of data, and transmitting one of the second sub-set of data and the third sub-set of data over the network for improving the fidelity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing predictive pre-recording of audio for voice input. In one aspect, a method includes obtaining sensor data from one or more sensors of a mobile device while the mobile device is operating in an inactive state, determining that a user of the mobile device is interacting with the mobile device based on the sensor data, invoking voice input functionality of the mobile device in response to determining that the user of the mobile device is interacting with the mobile device, detecting a voice input, and activating the mobile device in response to detecting the voice input.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing speech recognition accuracy. In one aspect, a method includes receiving an audio signal that corresponds to an utterance recorded by a mobile device, determining a geographic location associated with the mobile device, adapting one or more acoustic models for the geographic location, and performing speech recognition on the audio signal using the one or more acoustic models model that are adapted for the geographic location.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing predictive pre-recording of audio for voice input. In one aspect, a method includes establishing, as input data, state data that references a state of a mobile device and sensor data that is sensed by one or more sensors of the mobile device, applying a rule or a probabilistic model to the input data, inferring, based on applying the rule or the probabilistic model to the input data, that a user of the mobile device is likely to initiate voice input, and invoking one or more functionalities of the mobile device in response to inferring that the user is likely to initiate voice input.