Abstract: A request including audio data is received from a voice-enabled device. A string of phonemes present in the utterance is determined through speech recognition. At a later time, a subsequent user input corresponding to the request may be received, in which the user input is associated with one or more text keywords. The subsequent user input may be obtained in response to an active request. Alternatively, feedback may not be actively elicited, but rather collected passively. However it is obtained, the one or more keywords associated with the subsequent user input may be associated with the string of phonemes to indicate that the user is saying or mean those words when they product that string of phonemes. A user-specific speech recognition key for the user account is then updated to associate the string of phonemes with these words. A general speech recognition model can also be trained using the association.

Abstract: In various embodiments, a voice command is associated with a plurality of processing steps to be performed. The plurality of processing steps may include analysis of audio data using automatic speech recognition, generating and selecting a search query from the utterance text, and conducting a search of database of items using a search query. The plurality of processing steps may include additional or different steps, depending on the type of the request. In performing one or more of these processing steps, an error or ambiguity may be detected. An error or ambiguity may either halt the processing step or create more than one path of actions. A model may be used to determine if and how to request additional user input to attempt to resolve the error or ambiguity. The voice-enabled device or a second client device is then causing to output a request for the additional user input.

Abstract: Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.

Abstract: Contextual data corresponding to previous search requests of a service provider's electronic catalog can be used to resolve voice-input search requests and present search results. Contextual data includes the previous search request that is input to a machine learning algorithm along with a present search request. The machine learning algorithm generates a score indicative of whether the present search request is a refinement of the previous search or a new search request. Once the search request is classified as a refinement or a new search, the search is processed to provide search results including available items from the service provider matching the search request.

Abstract: A request including audio data is received from a voice-enabled device. A string of phonemes present in the utterance is determined through speech recognition. At a later time, a subsequent user input corresponding to the request may be received, in which the user input is associated with one or more text keywords. The subsequent user input may be obtained in response to an active request. Alternatively, feedback may not be actively elicited, but rather collected passively. However it is obtained, the one or more keywords associated with the subsequent user input may be associated with the string of phonemes to indicate that the user is saying or mean those words when they product that string of phonemes. A user-specific speech recognition key for the user account is then updated to associate the string of phonemes with these words. A general speech recognition model can also be trained using the association.

Abstract: Techniques for simulating a user in a conversation are described. A user simulation service and a conversation agent service conduct a dialog. The user simulation service compares a current sequence of stored labels corresponding to statements in the dialog with a plurality of candidate sequences of labels corresponding to statements in a plurality of candidate dialogs to identify a matching sequence of labels. The user simulation sequence identifies a base sequence of labels that includes the matching sequence of labels to identify a label corresponding to an act in the base sequence of labels following the matching sequence of labels. The user simulation service issues the act to the conversation agent service to be used as a simulated user act.

Abstract: Method, system, and programs for estimating interests of a plurality of users with respect to a new piece of information are disclosed. In one example, historical interests of the plurality of users are obtained with respect to one or more existing pieces of information. One or more users are selected from the plurality of users. Historical interests of the one or more users can minimize an objective function over the plurality of users. Interests of the one or more users are obtained with respect to the new piece of information. Estimated interests of the plurality of users are generated with respect to the new piece of information based on the obtained interests of the one or more users.

Abstract: Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate and/or support one or more operations and/or techniques for in part, to facilitate and/or support one or more operations and/or techniques for ranking answers for on-line community questions.

Abstract: Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.

Abstract: Briefly, example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate and/or support one or more operations and/or techniques for in part, to facilitate and/or support one or more operations and/or techniques for ranking answers for on-line community questions.

Abstract: Methods and devices for assessing the quality of user-generated content are described. In one embodiment, a method is disclosed for measuring the quality of a user-generated answer to a question by combining various factors, including question-answer surface word vector similarity, question-answer explicit semantic analysis vector similarity, answer-answer explicit sematic analysis vector similarity, query performance predictor, sentiment analysis, textual analysis of the answer, and reputation of the answerer. The method uses a learning procedure to determine the best algorithm for measuring the overall quality of the answer based on these factors.

Abstract: A content item presented to a user may involve two or more topics, such as news articles mentioning athletes or actors. Users may enjoy expressing opinions about a comparison of the topics, such as personal preferences or an evaluation of talent. Presented herein are techniques for automatically generating, for the content item, a poll among the topics of the content item. The respective comparisons of a comparison set are evaluated for the topics of the content item, and a comparison relevance score is computed identifying the relevance of the comparison of the topics. The comparison having the highest relevance for the topics is selected, and a comparison question is formulated and presented to the user with the content item. Results may be tabulated and presented for the topics of the content item. These techniques facilitate user expression about the content item without depending upon user-authored polls for each content item.

Abstract: A method for estimating model parameters. The method comprises receiving a data set related to a plurality of users and associated content, partitioning the data set into a plurality of sub data sets in accordance with the users so that data associated with each user are not partitioned into more than one sub data set, storing each of the sub data sets in a separate one of a plurality of user data storages, each of said data storages being coupled with a separate one of a plurality of estimators, storing content associated with the plurality of users in a content storage, where the content storage is coupled to the plurality of estimators so that the content in the content storage is shared by the estimators, and estimating, asynchronously by each estimator, one or more parameters associated with a model based on data from one of the sub data sets.

Abstract: A method for adjusting one or more parameters associated with a model. The method comprises obtaining, from a first source, first information related to activity of a user. The method further comprises adjusting one or more parameters associated with a model based on the first information collected within a first length of time, and obtaining, from a second source, second information related to activity of the user. The method further comprises adjusting the one or more parameters associated with the model based on the second information collected within a second length of time and a measure indicative of performance of the model, wherein the second length of time is larger than the first length of time.

Abstract: Method, system, and programs for estimating interests of a plurality of users with respect to a new piece of information are disclosed. In one example, historical interests of the plurality of users are obtained with respect to one or more existing pieces of information. One or more users are selected from the plurality of users. Historical interests of the one or more users can minimize an objective function over the plurality of users. Interests of the one or more users are obtained with respect to the new piece of information. Estimated interests of the plurality of users are generated with respect to the new piece of information based on the obtained interests of the one or more users.

Abstract: A content item presented to a user may involve two or more topics, such as news articles mentioning athletes or actors. Users may enjoy expressing opinions about a comparison of the topics, such as personal preferences or an evaluation of talent. Presented herein are techniques for automatically generating, for the content item, a poll among the topics of the content item. The respective comparisons of a comparison set are evaluated for the topics of the content item, and a comparison relevance score is computed identifying the relevance of the comparison of the topics. The comparison having the highest relevance for the topics is selected, and a comparison question is formulated and presented to the user with the content item. Results may be tabulated and presented for the topics of the content item. These techniques facilitate user expression about the content item without depending upon user-authored polls for each content item.

Abstract: A method for estimating model parameters. The method comprises receiving a data set related to a plurality of users and associated content, partitioning the data set into a plurality of sub data sets in accordance with the users so that data associated with each user are not partitioned into more than one sub data set, storing each of the sub data sets in a separate one of a plurality of user data storages, each of said data storages being coupled with a separate one of a plurality of estimators, storing content associated with the plurality of users in a content storage, where the content storage is coupled to the plurality of estimators so that the content in the content storage is shared by the estimators, and estimating, asynchronously by each estimator, one or more parameters associated with a model based on data from one of the sub data sets.

Abstract: A method for adjusting one or more parameters associated with a model. The method comprises obtaining, from a first source, first information related to activity of a user. The method further comprises adjusting one or more parameters associated with a model based on the first information collected within a first length of time, and obtaining, from a second source, second information related to activity of the user. The method further comprises adjusting the one or more parameters associated with the model based on the second information collected within a second length of time and a measure indicative of performance of the model, wherein the second length of time is larger than the first length of time.

Abstract: A circuit design, responsive the input signals, may be obtained and processed. The circuit design may define connections between combinational elements, memory elements, and input signals. Identification of cut-off points may be performed with respect to predetermined combinational logic input signals. The cut-off points may be connections whose values are not dependant on the value of the predetermined combinational logic input signals. An approximated circuit design may be synthesized by relaxing the logic associated with the cut-off points. Based on the approximated circuit design, processing may be performed. In some exemplary embodiments, a clock gating function of a memory element may be determined by approximating the circuit design with respect to the output signal of the memory element. The clock gating function may be determined based on the approximated circuit design and introduced to the circuit design, with or without additional refinement.