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    • 1. 发明申请
    • SOUND-BASED EVENT CONTROL USING TIMBRAL ANALYSIS
    • 基于声音的事件控制使用TIMBRAL分析
    • WO99049452A1
    • 1999-09-30
    • PCT/US1999/003747
    • 1999-03-17
    • G10H1/12G10H3/12G10H7/00
    • G10H1/125G10H3/125G10H2210/041G10H2210/066G10H2240/056G10H2250/221G10H2250/235
    • Arbitrary input sounds are analyzed and the coefficients of a low-dimensional representation, such as LPC or MFCC, are determined as a measure of the timbre of the sounds. The coefficients can be employed in different ways to control output events, such as the generation of synthesized sounds. In one approach, the individual coefficients (CO-C13) are mapped to the control parameters (24) of a sound synthesizer (28), to enable highly complex output sounds to be generated in response to simple input sounds. In another approach, pattern recognition techniques are employed with respect to the coefficients, to classify the input sounds. Each classification is mapped to a control parameter, to cause different events to occur in response to the respective input sounds. In one example, the sounds of different musical instruments are generated in dependence upon the classification of the input sounds. These analysis techniques have low latency, and thereby allow events to be controlled without perceptible delay.
    • 分析任意输入声音,并且将诸如LPC或MFCC的低维表示的系数确定为声音音色的度量。 系数可以以不同的方式用于控制输出事件,例如合成声音的产生。 在一种方法中,各个系数(CO-C13)被映射到声音合成器(28)的控制参数(24),以便响应于简单的输入声音而产生高度复杂的输出声音。 在另一种方法中,相对于系数使用模式识别技术来分类输入声音。 每个分类被映射到控制参数,以响应于相应的输入声音而导致不同的事件发生。 在一个示例中,根据输入声音的分类产生不同乐器的声音。 这些分析技术具有低延迟,从而允许事件被控制而没有可察觉的延迟。
    • 3. 发明申请
    • AUDIO ANALYSIS SYSTEM AND METHOD USING AUDIO SEGMENT CHARACTERISATION
    • 音频分析系统和使用音频分段特征的方法
    • WO2014096832A1
    • 2014-06-26
    • PCT/GB2013/053362
    • 2013-12-19
    • MAGAS, MichelaLAURIER, Cyril
    • MAGAS, MichelaLAURIER, Cyril
    • G10H1/00
    • G10H1/0008G10H2210/041G10H2210/061G10H2240/081G10H2240/085G10H2240/141G10H2250/235
    • A method of matching an input audio signal to one or more audio segments within a plurality of audio segments, the method comprising: receiving the input audio signal; processing the input audio signal to determine structural parameter feature data related to the received input audio signal; analysing the determined structural parameter feature data to extract semantic feature data; comparing the feature data of the input audio signal to pre-processed feature data relating to the plurality of audio segments in order to match one or more audio segments within a similarity threshold of the input audio signal; outputting a search result on the basis of the matched one or more audio segments wherein semantic feature data is extracted from the structural parameter data using a supervised learning technique.
    • 一种将输入音频信号与多个音频片段中的一个或多个音频片段相匹配的方法,所述方法包括:接收所述输入音频信号; 处理所述输入音频信号以确定与所接收的输入音频信号有关的结构参数特征数据; 分析确定的结构参数特征数据以提取语义特征数据; 将输入音频信号的特征数据与与多个音频段相关的预处理特征数据进行比较,以便匹配输入音频信号的相似性阈值内的一个或多个音频段; 基于使用监督学习技术从结构参数数据中提取语义特征数据的匹配的一个或多个音频段输出搜索结果。
    • 5. 发明申请
    • METHOD OF DERIVING A SET OF FEATURES FOR AN AUDIO INPUT SIGNAL
    • 为音频输入信号提供一组特征的方法
    • WO2007046048A1
    • 2007-04-26
    • PCT/IB2006/053787
    • 2006-10-16
    • KONINKLIJKE PHILIPS ELECTRONICS N.V.BREEBAART, Dirk, J.MCKINNEY, Martin, F.
    • BREEBAART, Dirk, J.MCKINNEY, Martin, F.
    • G10H1/00
    • G10H1/0008G10H2210/031G10H2210/041G10H2240/081
    • The invention describes a method of deriving a set of features (S) of an audio input signal (M), which method comprises identifying a number of first-order features (f 1 , f 2 , ... , f f ) of the audio input signal (M), generating a number of correlation values (ρ 1 , ρ 2 , ... , ρ I ) from at least part of the first-order features (f 1 , f 2 , ... , f f ), and compiling the set of features (S) for the audio input signal (M) using the correlation values (ρ 1 , ρ 2 , ..., ρ I ). The invention further describes a method of classifying an audio input signal (M) into a group, and a method of comparing audio input signals (M, M') to determine a degree of similarity between the audio input signals (M, M'). The invention also describes a system (1) for deriving a set of features (S) of an audio input signal (M), a classifying system (4) for classifying an audio input signal (M) into a group, and a comparison system (5) for comparing audio input signals (M, M') to determine a degree of similarity between the audio input signals (M, M').
    • 本发明描述了一种导出音频输入信号(M)的一组特征(S)的方法,该方法包括识别多个一阶特征(f 1,...,f 2) 音频输入信号(M)的多个相关值(α<1>,&lt; 2&gt;,&lt; 从第一阶特征(f 1 1,f 2,...,N 2)的至少一部分, ...,f&lt; f&lt;&gt;),并且使用相关值(α&lt; 1&lt; 1&lt; 1&gt;,&lt; SUB)来编译音频输入信号(M)的特征(S) > 2 ,...,... )。 本发明还描述了一种将音频输入信号(M)分类成一组的方法,以及一种比较音频输入信号(M,M')以确定音频输入信号(M,M')之间的相似程度的方法, 。 本发明还描述了一种用于导出音频输入信号(M)的一组特征(S)的系统(1),用于将音频输入信号(M)分类成一组的分类系统(4)和比较系统 (5),用于比较音频输入信号(M,M')以确定音频输入信号(M,M')之间的相似度。
    • 7. 发明申请
    • SIMILARITY DETERMINATION AND SELECTION OF MUSIC
    • 音乐的相似性决定与选择
    • WO2016102738A1
    • 2016-06-30
    • PCT/FI2014/051037
    • 2014-12-22
    • NOKIA TECHNOLOGIES OY
    • ERONEN, AnttiLEPPÄNEN, JussiSAARI, PasiLEHTINIEMI, Arto
    • G06F17/30G06K9/62
    • G06F17/3074G06K9/00536G06K9/6269G06K9/6292G06K9/685G10H1/0008G10H2210/036G10H2210/041G10H2210/056G10H2240/141
    • A method comprises determining properties of first group of music tracks, e.g. by a first artist,and a second group of music tracks, e.g. by a second artist,based on track level attributes, determining a similarity between the first and second groups based at least in part on determined properties of the tracks, selecting one or more tracks from the second group based at least in part on said similarity, and outputting a list of said selected tracks. The similarity may include group level, track level, and combined group and track level similarities. The track level attributes may be acoustic features extracted from the tracks, tags, metadata or other data, such as keywords extracted from reviews of the tracks. The method may include ranking and/or revising the list based on one or more of user preferences, a user history and/or whether a user plays or skips the selected tracks.
    • 一种方法包括确定第一组音乐曲目的属性,例如。 由第一艺术家和第二组音乐曲目组成。 由第二艺术家基于轨道级属性,至少部分地基于确定的轨道的属性来确定第一和第二组之间的相似性,至少部分地基于所述相似性从第二组中选择一个或多个轨道, 并输出所述所选轨道的列表。 相似度可以包括组级,跟踪级别以及组合和跟踪级别的相似度。 轨道级属性可以是从轨道,标签,元数据或其他数据提取的声学特征,例如从轨道的评论中提取的关键字。 该方法可以包括基于一个或多个用户偏好,用户历史和/或用户是播放或跳过所选择的轨道来排序和/或修改列表。
    • 10. 发明申请
    • MUSIC ANALYSIS
    • 音乐分析
    • WO2007029002A2
    • 2007-03-15
    • PCT/GB2006/003324
    • 2006-09-08
    • UNIVERSITY OF EAST ANGLIACOX, StephenWEST, Kris
    • COX, StephenWEST, Kris
    • G06F17/30G10H1/00
    • G06F17/30746G06F17/30743G10H1/0008G10H2210/041G10H2210/051G10H2210/061G10H2210/086G10H2240/081G10H2240/131G10H2250/311
    • There is disclosed an analyser (101) for building a transcription model (112; 500) using a training database (111) of music. The analyser (101) decomposes the training music (111) into sound events (201a-e) and, in one embodiment, allocates the sound events to leaf nodes (504a-h) of a tree (500). There is also disclosed a transcriber (102) for transcribing music (121) into a transcript (113). The transcript (113) is sequence of symbols that represents the music (121), where each symbol is associated with a sound event in the music (121) being transcribed. In one embodiment, the transcriber (102) associates each of the sound events (201a-e) in the music (121) with a leaf node (504a-h) of a tree (500); in this embodiment the transcript (113) is a list of the leaf nodes (504a-h). The transcript (113) preserves information regarding the sequence of the sound events (201a-e) in the music (121) being transcribed.
    • 公开了一种使用音乐的训练数据库(111)来构建转录模型(112; 500)的分析器(101)。 分析器(101)将训练音乐(111)分解为声音事件(201a-e),并且在一个实施例中,将声音事件分配给树(500)的叶节点(504a-h)。 还公开了用于将音乐(121)转录成抄本(113)的抄录器(102)。 成绩单(113)是表示音乐(121)的符号序列,其中每个符号与被转录的音乐(121)中的声音事件相关联。 在一个实施例中,转录器(102)将音乐(121)中的每个声音事件(201a-e)与树(500)的叶节点(504a-h)相关联; 在该实施例中,转录本(113)是叶节点(504a-h)的列表。 转录本(113)保存关于正在转录的音乐(121)中的声音事件(201a-e)的顺序的信息。