Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.

Abstract: Computer implemented speech processing generates one or more pronunciations of an input word in a first language by a non-native speaker of the first language who is a native speaker of a second language. The input word is converted into one or more pronunciations. Each pronunciation includes one or more phonemes selected from a set of phonemes associated with the second language. Each pronunciation is associated with the input word in an entry in a computer database. Each pronunciation in the database is associated with information identifying a pronunciation language and/or a phoneme language.

Abstract: Methods and systems for beam forming an audio signal based on a location of an object relative to the listening device, the location being determined from positional data deduced from an optical image including the object. In an embodiment, an object's position is tracked based on video images of the object and the audio signal received from a microphone array located at a fixed position is filtered based on the tracked object position. Beam forming techniques may be applied to emphasize portions of an audio signal associated with sources near the object.

Abstract: Methods for dynamically analyzing input sounds and processing the input sounds to define a new set of output sounds are provided. One method includes receiving a first set of input sounds and a second set of input sounds, where each of the first and second sets of input sounds are processed to identify one of a tone, intensity, or frequency, and a duration. The method defines a node for each identified input sound and a link between the input sounds of the first and second sets of input sounds. The nodes and links from the first and second sets of input sounds create a respective first and second finite state automata. A history value is defined for processing the nodes of the first and second sets of input sounds, and the history value defines a number of previous nodes that will be identical in each of the first and second sets of input sounds before a particular node is shared between the first and second sets of input sounds.

Abstract: Methods and systems for beam forming an audio signal based on a location of an object relative to the listening device, the location being determined from positional data deduced from an optical image including the object. In an embodiment, an object's position is tracked based on video images of the object and the audio signal received from a microphone array located at a fixed position is filtered based on the tracked object position. Beam forming techniques may be applied to emphasize portions of an audio signal associated with sources near the object.

Abstract: A speech recognition engine is provided with an acoustic model and a layered grammar and dictionary library. The layered grammar and dictionary library includes a language and non-grammar layer that supplies types of rules a grammar definition layer can use and defines non-grammar the speech recognition engine should ignore. The layered grammar and dictionary library also includes a dictionary layer that defines phonetic transcriptions for word groups the speech recognition engine is meant to recognize when voice input is received. The layered grammar and dictionary library further includes a grammar definition layer that applies rules from the language and non-grammar layer to define combinations of word groups the speech recognition system is meant to recognize. Voice input is received at a speech recognition engine and is processed using the acoustic model and the layered grammar and dictionary library.

Abstract: A speech recognition engine is provided with an acoustic model and a layered grammar and dictionary library. The layered grammar and dictionary library includes a language and non-grammar layer that supplies types of rules a grammar definition layer can use and defines non-grammar the speech recognition engine should ignore. The layered grammar and dictionary library also includes a dictionary layer that defines phonetic transcriptions for word groups the speech recognition engine is meant to recognize when voice input is received. The layered grammar and dictionary library further includes a grammar definition layer that applies rules from the language and non-grammar layer to define combinations of word groups the speech recognition system is meant to recognize. Voice input is received at a speech recognition engine and is processed using the acoustic model and the layered grammar and dictionary library.

Abstract: Methods for dynamically analyzing input sounds and processing the input sounds to define a new set of output sounds are provided. One method includes receiving a first set of input sounds and a second set of input sounds, where each of the first and second sets of input sounds are processed to identify one of a tone, intensity, or frequency, and a duration. The method defines a node for each identified input sound and a link between the input sounds of the first and second sets of input sounds. The nodes and links from the first and second sets of input sounds create a respective first and second finite state automata. A history value is defined for processing the nodes of the first and second sets of input sounds, and the history value defines a number of previous nodes that will be identical in each of the first and second sets of input sounds before a particular node is shared between the first and second sets of input sounds.

Abstract: Methods for optimizing grammar structure for a set of phrases to be used in speech recognition during a computing event are provided. One method includes receiving a set of phrases, the set of phrases being relevant for the computing event and the set of phrases having a node and link structure. Also included is identifying redundant nodes by examining the node and link structures of each of the set of phrases so as to generate a single node for the redundant nodes. The method further includes examining the node and link structures to identify nodes that are capable of being vertically grouped and grouping the identified nodes to define vertical word groups. The method continues with fusing nodes of the set of phrases that are not vertically grouped into fused word groups. Wherein the vertical word groups and the fused word groups are linked to define an optimized grammar structure.

Abstract: In one embodiment, a method for the automatic composition of music is disclosed. The method begins by receiving a plurality of input sound sequences containing sound frequencies with corresponding time duration. The method continues with converting the plurality of input sound sequences to a finite state automaton using a system that allows over-generation, followed by receiving exploration rules that constrain how the finite state automaton is to be traversed. The next step is creating a path marker data structure indexing a plurality of path markers, where each path marker contains a path marker history and a path marker registry. After the path marker data structure is created, the method continues by traversing the finite state automaton with a graph exploration procedure that uses the exploration rules and the plurality of path markers to determine paths across the finite state automaton.

Abstract: Computer implemented speech processing generates one or more pronunciations of an input word in a first language by a non-native speaker of the first language who is a native speaker of a second language. The input word is converted into one or more pronunciations. Each pronunciation includes one or more phonemes selected from a set of phonemes associated with the second language. Each pronunciation is associated with the input word in an entry in a computer database. Each pronunciation in the database is associated with information identifying a pronunciation language and/or a phoneme language.

Abstract: A system and method for an automatic set-up of speech recognition engines may include a speech recognizer configured to perform speech recognition procedures to identify input speech data according to one or more operating parameters. A merit manager may be utilized to automatically calculate merit values corresponding to the foregoing recognition procedures. These merit values may incorporate recognition accuracy information, recognition speed information, and a user-specified weighting factor that shifts the relative effect of the recognition accuracy information and the recognition speed information on the merit values. The merit manager may then automatically perform a merit value optimization procedure to select operating parameters that correspond to an optimal one of the merit values.

Abstract: A system and method for effectively performing speech recognition procedures includes enhanced demiphone acoustic models that a speech recognition engine utilizes to perform the speech recognition procedures. The enhanced demiphone acoustic models each have three states that are collectively arranged to form a preceding demiphone and a succeeding demiphone. An acoustic model generator may utilize a decision tree for analyzing speech context information from a training database. The acoustic model generator then effectively configures each of the enhanced demiphone acoustic models as either a succeeding-dominant enhanced demiphone acoustic model or a preceding-dominant enhanced demiphone acoustic model to accurately model speech characteristics.

Abstract: A system and method for utilizing speech recognition to efficiently perform data indexing procedures includes an authoring module that coordinates an authoring procedure for creating an index file that has pattern word sets corresponding to data objects stored in a memory of a host electronic device. The pattern word sets are generated with a speech recognition engine that transforms spoken data descriptions into text data descriptions for creating the pattern word sets. The pattern word sets are associated in the index file with data object identifiers that uniquely identify the corresponding data objects. A retrieval module manages a retrieval procedure in which the speech recognition engine converts a spoken data request into a text data request. The retrieval module compares the text data request and the pattern word sets to identify a requested object identifier for locating a requested data object from among the data objects stored in the memory of the host electronic device.

Abstract: A system and method for performing a refinement procedure to effectively implement a speech recognition dictionary for spontaneous speech recognition may include a problematic word identifier configured to divide vocabulary words from an initial speech recognition dictionary into problematic words and non-problematic words according to pre-defined identification criteria. A candidate generator may analyze the problematic words to produce one or more pronunciation candidates for each of the problematic words. An optimization module may then perform an optimization process for refining one or more pronunciation candidates according to certain optimization criteria to thereby generate optimized problematic pronunciations. A dictionary refinement manager may finally combine the optimized problematic pronunciations with non-problematic pronunciations of the non-problematic words to produce a refined speech recognition dictionary for use by the speech recognition system.

Abstract: Consumer electronic devices have been developed with enormous information processing capabilities, high quality audio and video outputs, large amounts of memory, and may also include wired and/or wireless networking capabilities. Additionally, relatively unsophisticated and inexpensive sensors, such as microphones, video camera, GPS or other position sensors, when coupled with devices having these enhanced capabilities, can be used to detect subtle features about users and their environments. A variety of audio, video, simulation and user interface paradigms have been developed to utilize the enhanced capabilities of these devices. These paradigms can be used separately or together in any combination. One paradigm automatically creating user identities using speaker identification. Another paradigm includes a control button with 3-axis pressure sensitivity for use with game controllers and other input devices.