Abstract: The present invention relates to a part of a binding system for skiing, comprising a housing (3; 8) with, on the inside, a fully or partially through-going axial barrel (13) with an inner diameter (14), wherein two pins (1) moveable in each direction with at least one intermediate spring element (2) are arranged, and wherein the pins (1) are adapted to slide in the barrel (13) between a protruding and a retracted position. According to an aspect of the invention, the part of the pins (1) that is exposed when the pins (1) are in the protruding position, has a reduced outer diameter (15) compared with the inner diameter (14) of the barrel (13). The invention also relates to a method for lubricating the pins (1) with a lubricant.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: Table of contents (TOC) information contained in an audio CD is used to generate a TOC print which may be used for identifying the CD. The TOC print is generated based on the lengths of the tracks contained in the CD. A track vector is generated based on each track length and a matrix is created using the generated track vectors. A singular value decomposition (SVD) computation is performed on the matrix for decomposing the matrix into a set of linearly independent basis vectors. One or more of the basis vectors are selected and set as the TOC print for the CD. Once the TOC print has been generated, the TOC print may be compared against the TOC prints of known CDs in a central database to retrieve from the database metadata information stored in association with the known CDs.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: An audio fingerprinting system and method. A server receives an audio fingerprint of a first audio piece, searches a database for the audio fingerprint, retrieves an audio profile vector associated with the audio fingerprint, updates user preference information based on the audio profile vector, and selects a second audio piece based on the user preference information. The audio fingerprint is generated by creating a matrix based on the frequency measurements of the audio piece, and performing a singular value decomposition of the matrix. To expedite the search of the database and to increase matching accuracy, a subset of candidates in the database is identified based on the most prominent musical notes of the audio piece, and the search is limited to the identified subset. One of the attributes of the audio profile vector is a particular audio class. An identifier for the audio class is generated based on an average of audio fingerprints of the audio pieces belonging to the audio class.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: An audio fingerprinting system and method. A server receives an audio fingerprint of a first audio piece, searches a database for the audio fingerprint, retrieves an audio profile vector associated with the audio fingerprint, updates user preference information based on the audio profile vector, and selects a second audio piece based on the user preference information. The audio fingerprint is generated by creating a matrix based on the frequency measurements of the audio piece, and performing a singular value decomposition of the matrix. To expedite the search of the database and to increase matching accuracy, a subset of candidates in the database is identified based on the most prominent musical notes of the audio piece, and the search is limited to the identified subset. One of the attributes of the audio profile vector is a particular audio class. An identifier for the audio class is generated based on an average of audio fingerprints of the audio pieces belonging to the audio class.

Abstract: An audio fingerprinting system and method. A server receives an audio fingerprint of a first audio piece, searches a database for the audio fingerprint, retrieves an audio profile vector associated with the audio fingerprint, updates user preference information based on the audio profile vector, and selects a second audio piece based on the user preference information. The audio fingerprint is generated by creating a matrix based on the frequency measurements of the audio piece, and performing a singular value decomposition of the matrix. To expedite the search of the database and to increase matching accuracy, a subset of candidates in the database is identified based on the most prominent musical notes of the audio piece, and the search is limited to the identified subset. One of the attributes of the audio profile vector is a particular audio class. An identifier for the audio class is generated based on an average of audio fingerprints of the audio pieces belonging to the audio class.

Abstract: An audio fingerprinting system and method. A server receives an audio fingerprint of a first audio piece, searches a database for the audio fingerprint, retrieves an audio profile vector associated with the audio fingerprint, updates user preference information based on the audio profile vector, and selects a second audio piece based on the user preference information. The audio fingerprint is generated by creating a matrix based on the frequency measurements of the audio piece, and performing a singular value decomposition of the matrix. To expedite the search of the database and to increase matching accuracy, a subset of candidates in the database is identified based on the most prominent musical notes of the audio piece, and the search is limited to the identified subset. One of the attributes of the audio profile vector is a particular audio class. An identifier for the audio class is generated based on an average of audio fingerprints of the audio pieces belonging to the audio class.

Abstract: A music recommendation system receives a user selection of desired music, retrieves analysis data associated with the selected music, and generates a playlist of songs based on the analysis data. The analysis data is generated based on a processing of one or more audio signals associated with the selected music. The analysis data may downloaded from a central server. If the analysis data is not available from the central server, it is generated locally at a user end, and uploaded to the central server. A plurality of user-selectable shuffling mechanisms are provided to allow the order of the songs to be shuffled according to the selected shuffling mechanism. The end user device may also receive recommendation of new music from different providers based on the analysis data of music for which the recommendation is to be based.

Abstract: Prosody templates, constructed during system design, store intonation (F0) and duration information based on syllabic stress patterns for the target word. The prosody templates are constructed so that words exhibiting the same stress pattern will be assigned the same prosody template. The prosody template information is preferably stored in a normalized form to reduce noise level in the statistical measures. The synthesizer uses a word dictionary that specifies the stress patterns associated with each stored word. These stress patterns are used to access the prosody template database. F0 and duration information is then extracted from the selected template, de-normalized and applied to the phonemic information to produce a natural human-sounding prosody in the synthesized output.

Abstract: A method of separating high-level prosodic behavior from purely articulatory constraints so that timing information can be extracted from human speech is presented. The extracted timing information is used to construct duration templates that are employed for speech synthesis. The duration templates are constructed so that words exhibiting the same stress pattern will be assigned the same duration template. Initially, the words of input text segmented into phonemes and syllables, and the associated stress pattern is assigned. The stress assigned words are then assigned grouping features by a text grouping module. A phoneme cluster module groups the phonemes into phoneme pairs and single phonemes. A static duration associated with each phoneme pair and single phoneme is retrieved from a global static table. A normalization module generates a normalized syllable duration value based upon the retrieved static durations associated with the phonemes that comprise the syllable.

Abstract: An application-independent, text-to-speech control system which employs an easy-to-use transport from which a user can control most text-to-speech conversion functions without prior training. It provides a control means by which user designated areas may be sequentially selected, stored and played. Furthermore, moving back and forward through user-selected text may be controlled by the user, with the synthesized speech output maintaining the proper pauses and inflections.