Abstract: Methods, computer program products and systems are described for converting speech to text. Sound information is received at a computer server system from an electronic device, where the sound information is from a user of the electronic device. A context identifier indicates a context within which the user provided the sound information. The context identifier is used to select, from among multiple language models, a language model appropriate for the context. Speech in the sound information is converted to text using the selected language model. The text is provided for use by the electronic device.

Abstract: Methods, computer program products and systems are described for forming a speech recognition language model. Multiple query-website relationships are determined by identifying websites that are determined to be relevant to queries using one or more search engines. Clusters are identified in the query-website relationships by connecting common queries and connecting common websites. A speech recognition language model is created for a particular website based on at least one of analyzing at queries in a cluster that includes the website or analyzing webpage content of web pages in the cluster that includes the website.

Abstract: Methods, computer program products and systems are described for speech-to-text conversion. A voice input is received from a user of an electronic device and contextual metadata is received that describes a context of the electronic device at a time when the voice input is received. Multiple base language models are identified, where each base language model corresponds to a distinct textual corpus of content. Using the contextual metadata, an interpolated language model is generated based on contributions from the base language models. The contributions are weighted according to a weighting for each of the base language models. The interpolated language model is used to convert the received voice input to a textual output. The voice input is received at a computer server system that is remote to the electronic device. The textual output is transmitted to the electronic device.

Abstract: Methods, computer program products and systems are described for forming a speech recognition language model. Multiple query-website relationships are determined by identifying websites that are determined to be relevant to queries using one or more search engines. Clusters are identified in the query-website relationships by connecting common queries and connecting common websites. A speech recognition language model is created for a particular website based on at least one of analyzing at queries in a cluster that includes the website or analyzing webpage content of web pages in the cluster that includes the website.

Abstract: A computer-implemented input-method editor process includes receiving a request from a user for an application-independent input method editor having written and spoken input capabilities, identifying that the user is about to provide spoken input to the application-independent input method editor, and receiving a spoken input from the user. The spoken input corresponds to input to an application and is converted to text that represents the spoken input. The text is provided as input to the application.

Abstract: Methods, computer program products and systems are described for converting speech to text. Sound information is received at a computer server system from an electronic device, where the sound information is from a user of the electronic device. A context identifier indicates a context within which the user provided the sound information. The context identifier is used to select, from among multiple language models, a language model appropriate for the context. Speech in the sound information is converted to text using the selected language model. The text is provided for use by the electronic device.

Abstract: An approach to multi-lingual speech recognition that permits different words in an utterance to be from different languages. Words from different languages are represented using different sets of sub-word units that are each associate with the corresponding language. Despite the use of different sets of sub-word units, the approach enables use of cross-word context at boundaries between words from different languages (cross-language context) to select appropriate variants of the sub-word units to match the context.

Abstract: A method of speech recognition is described for use with mobile user devices. A speech signal representative of input speech is forwarded from a mobile user device to a remote server. At the mobile user device, a speech recognition result representative of the speech signal is received from the remote server. The speech recognition result includes alternate recognition hypotheses associated with one or more portions of the speech recognition result. A user correction selection representing a portion of the speech recognition result is obtained from the user. The user is presented with selected alternate recognition hypotheses associated with the user correction selection. A user chosen one of the selected alternate recognition hypotheses is substituted for the user correction selection to form a corrected speech recognition result.

Abstract: A speech recognition system includes a user interface configured to provide signals indicative of a user's speech. A speech recognizer of the system includes a processor configured to use the signals from the user interface to perform speech recognition operations to attempt to recognize speech indicated by the signals. A control mechanism is coupled to the voice recognizer and is configured to affect processor usage for speech recognition operations in accordance with a loading of the processor.

Abstract: An approach to multi-lingual speech recognition that permits different words in an utterance to be from different languages. Words from different languages are represented using different sets of sub-word units that are each associate with the corresponding language. Despite the use of different sets of sub-word units, the approach enables use of cross-word context at boundaries between words from different languages (cross-language context) to select appropriate variants of the sub-word units to match the context.

Abstract: A speech recognition system includes a user interface configured to provide signals indicative of a user's speech. A speech recognizer of the system includes a processor configured to use the signals from the user interface to perform speech recognition operations to attempt to recognize speech indicated by the signals. A control mechanism is coupled to the voice recognizer and is configured to affect processor usage for speech recognition operations in accordance with a loading of the processor.

Abstract: A speech recognition system includes a user interface configured to provide signals indicative of a user's speech. A speech recognizer of the system includes a processor configured to use the signals from the user interface to perform speech recognition operations to attempt to recognize speech indicated by the signals. A control mechanism is coupled to the voice recognizer and is configured to affect processor usage for speech recognition operations in accordance with a loading of the processor.

Abstract: The invention includes a method for speech recognition using cross-word contexts on dynamic grammars. The invention also includes a method for constructing a speech recognizer capable of speech recognition using cross-word contexts on dynamic grammars, by expanding a word of the main grammar into a corresponding network of sub-word units. The sub-word units are selected from the plurality of sub-word units based in part on a pronunciation of the word. Each sub-word unit has a permissible context including constraints on neighboring sub-word units within the corresponding network. The corresponding network is chosen to satisfy the constraints of the permissible context of each sub-word unit within the corresponding network. When the context of sub-word units would have apply to words provided by a runtime grammar, the expansion includes every sub-word unit that satisfies the permissible context, when compared to the corresponding network.

Abstract: Pre-computed context-dependent phoneme representations of a number of constituents of a grammar are processed dynamically by a speech recognizer. The approach provides a configurable tradeoff between data size and recognition-time computation. This tradeoff can be obtained without sacrificing recognition accuracy, and in particular, allows full modeling of all cross-word phoneme contexts. In one aspect of the invention, a specification of a grammar is processed. This specification includes specifications of a number of constituents of the grammar. A first subset of the constituents of the grammar are selected, and the remaining of the constituents form a second subset. For each of the constituents in the first subset the method first includes processing the specification of the constituent to form a first processed representation that defines sequences of elements that are associated with that constituent and that includes words and references to constituents in the first subset.