Abstract: Methods are provided for ordering semantically-identified query formulation suggestions. Semantic query patterns are identified for a plurality of search queries and a weight is identified for each. Also identified is a plurality of semantic categories, each having an identified weight. Terms/phrases commonly associated with the semantic categories are identified, as are semantic attributes as they pertain to the semantic categories. Semantic attribute patterns and respective weights therefore are identified. A text-parser is generated from the semantic query patterns and respective weights, the semantic category terms, and the semantic attribute patterns and respective weights, the text-parser for use in parsing input user queries or portions thereof.

Abstract: Online spelling correction/phrase completion is described herein. A computer-executable application receives a phrase prefix from a user, wherein the phrase prefix includes a first character sequence. A transformation probability is retrieved responsive to receipt of the phrase prefix, wherein the transformation probability indicates a probability that a second character sequence has been transformed into a first character sequence. A search is then executed over a trie to locate a most probable phrase completion based at least in part upon the transformation probability.

Abstract: The present invention is directed to presenting a suggested search query. Responsive to receiving a user-devised search parameter, a suggested search query is identified. The user-devised search parameter might have been previously received by a search system, or alternatively, might be a unique query that has not been previously received. A suggested search query might be generated using various techniques, such as by applying an n-gram language model. A classification of the suggested search query is determined, and the suggested search query is presented together with a visual indicator, which signifies the classification.

Abstract: A resource selection system is described for assisting a user in performing a task that includes multiple actions. At each stage of the task, the system presents a set resources from which the user may select to perform a subsequent action in the task. The system implicitly selects the set of resources based on context information that identifies the user's current informational needs. For example, the context information may be derived from textual information that is being presented on a user device, which the user is presumed to be viewing at the current time. In one implementation, the system selects the set of resources by computing language models for respective domains and respective entities. The system uses the language models to determine the relevance of the context information to each of the domains. The system then selects resources associated with domains that have been assessed as relevant.

Abstract: A potential user query that can be subsequently received from a user is identified. An interface exposed by a data service is invoked, which includes providing the potential user query to the interface. Search results in response to the potential user query are received from the interface and maintained in a complex data set store. If a user query is subsequently received that maps to a normalized query that is the potential user query, then search results for the normalized query are obtained from the complex data set store and returned as the search results for the user query.

Abstract: Architecture that employs a modeling technique based on language modeling to estimate a probability of a document matching the user need as expressed in the query. The modeling technique is based on the data mining results that various portions of a document (e.g., body, title, URL, anchor text, user queries) use different styles of human languages. Thus, the results based on a language can be adapted individually to match the language of query. Since the approach is based on adaptation, the framework also provides a natural means to progressively revise the model as user data are collected. Different styles of languages in a document can be recognized and adapted individually. Background language models are also employed that offer a fallback approach in case the document has incomplete fields of data, and can utilize topical or semantic hierarchy of the knowledge domain.

Abstract: A method of entering information into a mobile device includes receiving a multi-word speech input from a user, performing speech recognition on the speech input to obtain a multi-word speech recognition result, and sequentially displaying, in a display, words in the speech recognition result for user confirmation or correction, by adding one word at a time to the display. A next word is only displayed after user confirmation or correct has been received for a previously displayed word that is immediately preceding the next word in the speech recognition result. The method also includes calculating a hypothesis lattice indicative of a plurality of speech recognition hypotheses based on the speech input and, prior to finishing calculating the hypothesis lattice and while continuing to calculate the hypothesis lattice, calculating a preliminary hypothesis lattice indicative of only partial speech recognition hypotheses based on the speech input and outputting the preliminary hypotheses lattice.

Abstract: Speech recognition utilizing categories and prefixes is disclosed. Categories identify types of recognition and allow different grammars and prefixes for each category. Categories can be directed to specific applications and/or program modules. Uttering a prefix allows users to easily direct text to specific grammars for enhanced recognition, and also to direct the recognized text to the appropriate application/module.

Abstract: Both speech and alternate modality inputs are used in inputting information spoken into a mobile device. The alternate modality inputs can be used to perform sequential commitment of words in a speech recognition result.

Abstract: Speech recognition utilizing categories and prefixes is disclosed. Categories identify types of recognition and allow different grammars and prefixes for each category. Categories can be directed to specific applications and/or program modules. Uttering a prefix allows users to easily direct text to specific grammars for enhanced recognition, and also to direct the recognized text to the appropriate application/module.

Abstract: The present invention provides an object model that exposes speech-related functionality to applications that target a managed code environment. In one embodiment, the object model and associated interfaces are implemented consistently with other non-speech related interfaces supported across a platform.