Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: A system and method for conducting electronic commerce are disclosed. In various embodiments, the electronic transaction is a purchase transaction. A user is provided with an intelligent token, such as a smartcard containing a digital certificate. The intelligent token suitably authenticates with a server on a network that conducts all or portions of the transaction on behalf of the user. In various embodiments a wallet server interacts with a security server to provide enhanced reliability and confidence in the transaction. In various embodiments, the wallet server includes a toolbar. In various embodiments, the digital wallet pre-fills forms. Forms may be pre-filled using an auto-remember component.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: A system and method for conducting electronic commerce are disclosed. In various embodiments, the electronic transaction is a purchase transaction. A user is provided with an intelligent token, such as a smartcard containing a digital certificate. The intelligent token suitably authenticates with a server on a network that conducts all or portions of the transaction on behalf of the user. In various embodiments a wallet server interacts with a security server to provide enhanced reliability and confidence in the transaction. In various embodiments, the wallet server includes a toolbar. In various embodiments, the digital wallet pre-fills forms. Forms may be pre-filled using an auto-remember component.

Abstract: Systems, methods, and computer program products are provided for editing digital audio data. In some implementations a method is provided that includes receiving digital audio data, identifying a modification to a portion of the digital audio data, and automatically correcting audio data surrounding one or more edit boundaries resulting from the identified modification including interpolating audio data from a region associated with the one or more edit boundaries.

Abstract: This specification describes technologies relating to editing digital audio data. In some implementations, a computer-implemented method is provided. The method includes displaying a visual representation of audio data, receiving an image, positioning the image as overlapping a portion of the displayed visual representation of the audio data, and editing the audio data corresponding to the portion of the displayed visual representation of the audio data overlapped by the image to form edited audio data, the editing including applying a variable editing effect according to the image content. In other implementations a computer-implemented method is provided that includes receiving an image, converting the image into a display of a visual representation of audio data using a specified conversion mode, and storing audio data corresponding to the display of audio data.

Abstract: The derivation of personalized HRTFs for a human subject based on the anthropometric feature parameters of the human subject involves obtaining multiple anthropometric feature parameters and multiple HRTFs of multiple training subjects. Subsequently, multiple anthropometric feature parameters of a human subject are acquired. A representation of the statistical relationship between the plurality of anthropometric feature parameters of the human subject and a subset of the multiple anthropometric feature parameters belonging to the plurality of training subjects is determined. The representation of the statistical relationship is then applied to the multiple HRTFs of the plurality of training subjects to obtain a set of personalized HRTFs for the human subject.

Abstract: This specification describes technologies relating to editing digital audio data. In some implementations, a computer-implemented method is provided. The method includes displaying a visual representation of audio data, receiving an image, positioning the image as overlapping a portion of the displayed visual representation of the audio data, and editing the audio data corresponding to the portion of the displayed visual representation of the audio data overlapped by the image to form edited audio data, the editing including applying a variable editing effect according to the image content. In other implementations a computer-implemented method is provided that includes receiving an image, converting the image into a display of a visual representation of audio data using a specified conversion mode, and storing audio data corresponding to the display of audio data.

Abstract: Systems, methods, and computer program products are provided for editing digital audio data. In some implementations a method is provided that includes receiving digital audio data, identifying a modification to a portion of the digital audio data, and automatically correcting audio data surrounding one or more edit boundaries resulting from the identified modification including interpolating audio data from a region associated with the one or more edit boundaries.

Abstract: A system and method for conducting electronic commerce are disclosed. In various embodiments, the electronic transaction is a purchase transaction. A user is provided with an intelligent token, such as a smartcard containing a digital certificate. The intelligent token suitably authenticates with a server on a network that conducts all or portions of the transaction on behalf of the user. In various embodiments a wallet server interacts with a security server to provide enhanced reliability and confidence in the transaction. In various embodiments, the wallet server includes a toolbar. In various embodiments, the digital wallet pre-fills forms. Forms may be pre-filled using an auto-remember component.

Abstract: A system and method for conducting electronic commerce are disclosed. In various embodiments, the electronic transaction is a purchase transaction. A user is provided with an intelligent token, such as a smartcard containing a digital certificate. The intelligent token suitably authenticates with a server on a network that conducts all or portions of the transaction on behalf of the user. In various embodiments a wallet server interacts with a security server to provide enhanced reliability and confidence in the transaction. In various embodiments, the wallet server includes a toolbar. In various embodiments, the digital wallet pre-fills forms. Forms may be pre-filled using an auto-remember component.

Abstract: Systems and methods for audio editing are provided. In one implementation, a computer-implemented method is provided. The method includes receiving digital audio data including a plurality of distinct vocal components. Each distinct vocal component is automatically identified using one or more attributes that uniquely identify each distinct vocal component. The audio data is separated into two or more individual tracks where each individual track comprises audio data corresponding to one distinct vocal component. The separated individual tracks are then made available for further processing.

Abstract: Systems and methods for audio editing are provided. In one implementation, a computer-implemented method is provided. The method includes receiving digital audio data including a plurality of distinct vocal components. Each distinct vocal component is automatically identified using one or more attributes that uniquely identify each distinct vocal component. The audio data is separated into two or more individual tracks where each individual track comprises audio data corresponding to one distinct vocal component. The separated individual tracks are then made available for further processing.

Abstract: Systems and methods for editing digital audio data are provided. In one implementation, a method is provided that includes receiving digital audio data. The computer implemented method includes receiving digital audio data and displaying a representation of the digital audio data. The method also includes receiving a selection including a portion of the digital audio data, analyzing a feature of the audio data for the selected portion with respect to a plurality of frequency bands in the digital audio data, calculating a feature value for each frequency band over a specified period of time, and using the feature value for each frequency band to adjust the feature of the audio data.

Abstract: A system and method for conducting electronic commerce are disclosed. In various embodiments, the electronic transaction is a purchase transaction. A user is provided with an intelligent token, such as a smartcard containing a digital certificate. The intelligent token suitably authenticates with a server on a network that conducts all or portions of the transaction on behalf of the user. In various embodiments a wallet server interacts with a security server to provide enhanced reliability and confidence in the transaction. In various embodiments, the wallet server includes a toolbar. In various embodiments, the digital wallet pre-fills forms. Forms may be pre-filled using an auto-remember component.