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    COMPLEX EVOLUTION RECURRENT NEURAL NETWORKS
    1.
    发明申请
    COMPLEX EVOLUTION RECURRENT NEURAL NETWORKS 审中-公开

    公开(公告)号：US20190156819A1

    公开(公告)日：2019-05-23

    申请号：US16251430

    申请日：2019-01-18

    申请人： Google LLC

    发明人： Izhak Shafran ,  Thomas E. Bagby ,  Russell John Wyatt Skerry-Ryan

    IPC分类号： G10L15/16 ,  G10L19/02 ,  G10L15/02 ,  G10H1/00

    CPC分类号： G10L15/16 ,  G06N3/02 ,  G10H1/00 ,  G10H2210/036 ,  G10H2210/046 ,  G10H2250/235 ,  G10H2250/311 ,  G10L15/02 ,  G10L17/18 ,  G10L19/0212 ,  G10L25/30

    摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for speech recognition using complex evolution recurrent neural networks. In some implementations, audio data indicating acoustic characteristics of an utterance is received. A first vector sequence comprising audio features determined from the audio data is generated. A second vector sequence is generated, as output of a first recurrent neural network in response to receiving the first vector sequence as input, where the first recurrent neural network has a transition matrix that implements a cascade of linear operators comprising (i) first linear operators that are complex-valued and unitary, and (ii) one or more second linear operators that are non-unitary. An output vector sequence of a second recurrent neural network is generated. A transcription for the utterance is generated based on the output vector sequence generated by the second recurrent neural network. The transcription for the utterance is provided.

    Music modeling
    2.
    发明授权
    Music modeling 有权

    公开(公告)号：US09934771B1

    公开(公告)日：2018-04-03

    申请号：US15629250

    申请日：2017-06-21

    申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

    发明人： Yachiko Obara ,  Shohei Ohsawa ,  Takayuki Osogami

    IPC分类号： G04B13/00 ,  G10H1/00

    CPC分类号： G10H1/0025 ,  G10H2210/061 ,  G10H2210/066 ,  G10H2210/145 ,  G10H2240/145 ,  G10H2250/005 ,  G10H2250/311

    摘要： A computer implemented method is provided for generating a prediction of a next musical note by a computer having at least a processor and a memory. A computer processor system is also provided for generating a prediction of a next musical note. The method includes storing sequential musical notes in the memory. The method further includes dividing, by the processor, the sequential musical notes into sections of a given length based on a Generative Theory of Tonal Music. The method also includes generating, by the processor, the prediction of the next musical note based upon a music model, the sections, and the sequential musical notes stored in the memory. The given length is determined based on one or more conditions.

    OPTICAL ELECTRIC GUITAR TRANSDUCER AND MIDI GUITAR CONTROLLER
    4.
    发明申请
    OPTICAL ELECTRIC GUITAR TRANSDUCER AND MIDI GUITAR CONTROLLER 审中-公开
    光电吉他传感器和MIDI吉他控制器

    公开(公告)号：US20120266740A1

    公开(公告)日：2012-10-25

    申请号：US13451124

    申请日：2012-04-19

    申请人： Nathan Hilbish ,  Afroditi Vennie Filippas ,  Lee Stewart ,  Andrew Good

    发明人： Nathan Hilbish ,  Afroditi Vennie Filippas ,  Lee Stewart ,  Andrew Good

    IPC分类号： G10H3/06 ,  G10H7/00

    CPC分类号： G10H3/06 ,  G10H3/125 ,  G10H3/146 ,  G10H2220/411 ,  G10H2250/311

    摘要： Photodiodes in combination with an amplifier of transimpedance configuration provides an optical vibration detector having a linear frequency response with a light emitter and sensor of sufficiently small size to be inserted between strings of a musical instrument in order to provide signals suitable for amplification. The frequencies of vibrating strings of a musical instrument can be converted in accordance with either of two converter embodiments to control a music synthesizer, an automatic music transcription arrangement or the like.

    摘要翻译： 与跨阻配置的放大器组合的光电二极管提供具有线性频率响应的光学振动检测器，其具有足够小尺寸的光发射器和传感器，以插入到乐器的弦之间，以便提供适合于放大的信号。 可以根据两个转换器实施例中的任一个来转换乐器的振动弦的频率以控制音乐合成器，自动音乐转录装置等。

    Autonomous Musical Output Using a Mutually Inhibited Neuronal Network
    5.
    发明申请
    Autonomous Musical Output Using a Mutually Inhibited Neuronal Network 审中-公开
    使用相互抑制神经网络的自主音乐输出

    公开(公告)号：US20070280270A1

    公开(公告)日：2007-12-06

    申请号：US10591828

    申请日：2004-03-11

    申请人： Pauli Laine ,  Juho Niemisto

    发明人： Pauli Laine ,  Juho Niemisto

    IPC分类号： H04L12/28

    CPC分类号： G10H1/0025 ,  G06N3/02 ,  G10H2210/111 ,  G10H2220/371 ,  G10H2250/311 ,  G10H2250/435

    摘要： A method of creating autonomous musical output: including creating a mutually inhibiting neuronal network including a plurality of nodes arranged to integrate and fire; associating each of the plurality of nodes with a musical instrument; and creating, when a node fires, a musical output corresponding to the musical instrument associated with the firing node.

    摘要翻译： 一种创建自主音乐输出的方法：包括创建一个相互抑制的神经网络，包括布置成整合和发射的多个节点; 将所述多个节点中的每一个与乐器相关联; 以及当节点触发时创建与与所述触发节点相关联的乐器相对应的音乐输出。

    Control structure for sound synthesis
    7.
    发明授权
    Control structure for sound synthesis 失效
    声音合成控制结构

    公开(公告)号：US5880392A

    公开(公告)日：1999-03-09

    申请号：US756935

    申请日：1996-12-02

    申请人： David Wessel ,  Michael Lee

    发明人： David Wessel ,  Michael Lee

    IPC分类号： G06F15/18 ,  G06N3/00 ,  G10H7/08 ,  G10H7/10 ,  G10L13/00 ,  G10H1/08 ,  G10H1/10

    CPC分类号： G10H7/10 ,  G10H2230/221 ,  G10H2230/351 ,  G10H2250/151 ,  G10H2250/235 ,  G10H2250/311 ,  G10H2250/625

    摘要： An improved control structure for music synthesis is provided in which: 1) the sound representation provided to the adaptive function mapper allows for a greatly increased degree of control over the sound produced; and 2) training of the adaptive function mapper is performed using an error measure, or error norm, that greatly facilitates learning while ensuring perceptual identity of the produced sound with the training example. In accordance with one embodiment of the invention, sound data is produced by applying to an adaptive function mapper control parameters including: at least one parameter selected from the set of time and timbre space coordinates; and at least one parameter selected from the set of pitch, .DELTA.pitch, articulation and dynamic. Using an adaptive function mapper, mapping is performed from the control parameters to synthesis parameters to be applied to a sound synthesizer. In accordance with another embodiment of the invention, an adaptive function mapper is trained to produce, in accordance with information stored in a mapping store, synthesis parameters to be applied to a sound synthesizer, by steps including: analyzing sounds to produce sound parameters describing the sounds; further analyzing the sound parameters to produce control parameters; applying the control parameters to the adaptive function mapper, the adaptive function mapper in response producing trial synthesis parameters comparable to the sound parameters; deriving from the sound parameters and the trial synthesis parameters an error measure in accordance with a perceptual error norm in which at least some error contributions are weighted in approximate degree to which they are perceived by the human ear during synthesis; and adapting the information stored in the mapping store in accordance with the error measure.

    摘要翻译： 提供了一种用于音乐合成的改进的控制结构，其中：1）提供给自适应功能映射器的声音表示允许对所产生的声音的大大增加的控制程度; 和2）使用误差测量或误差范数来执行自适应函数映射器的训练，其大大有助于学习，同时通过训练示例确保产生的声音的感知身份。 根据本发明的一个实施例，通过应用到自适应功能映射器控制参数来产生声音数据，所述自适应功能映射器控制参数包括：从所述时间集合和音色空间坐标中选择的至少一个参数; 以及从音调集，DELTA音调，关节和动态中选择的至少一个参数。 使用自适应函数映射器，从控制参数到要应用于声音合成器的合成参数进行映射。 根据本发明的另一实施例，训练自适应函数映射器，以便根据存储在映射存储器中的信息，通过以下步骤产生要应用于声音合成器的合成参数：包括：分析声音以产生描述 声音 进一步分析声音参数产生控制参数; 将控制参数应用于自适应函数映射器，自适应函数映射器响应于产生与声音参数相当的试验合成参数; 从声音参数和试验合成参数得出根据感知误差范数的误差测量，其中至少一些误差贡献在合成期间被人耳感知到的近似程度加权; 以及根据误差测量来适应存储在映射存储器中的信息。

    Synthesizer detecting pitch and plucking point of stringed instrument to generate tones
    8.
    发明授权
    Synthesizer detecting pitch and plucking point of stringed instrument to generate tones 失效
    合成器检测弦乐器的音高和采摘点，产生音调

    公开(公告)号：US5717155A

    公开(公告)日：1998-02-10

    申请号：US662474

    申请日：1996-06-13

    申请人： Andreas Szalay

    发明人： Andreas Szalay

    IPC分类号： G10H1/00 ,  G10H3/12 ,  G10H3/18 ,  G10H1/057 ,  G10H1/06

    CPC分类号： G10H3/125 ,  G10H3/188 ,  G10H2210/066 ,  G10H2210/225 ,  G10H2210/331 ,  G10H2240/056 ,  G10H2250/311 ,  G10H2250/625

    摘要： In an electronic musical apparatus having an acoustic instrument manually operable to commence an acoustic vibration and a tone generator responsive to the acoustic vibration to generate a musical tone having a pitch corresponding to that of the acoustic vibration, a pitch detecting device utilizes a pickup for picking up the acoustic vibration to convert the same into a waveform signal. Further, a first detector operates according to a fast algorithm for processing the waveform signal so as responsively produce a first output representative of the pitch of the acoustic vibration, and a second detector operates in parallel to the first detector for processing the same waveform signal according to a slow algorithm so as to stably produce a second output representative of the pitch of the acoustic vibration. A selector selectively feeds one of the first output and the second output to the tone generator so that the first detector and the second detector can cooperate to ensure responsive and stable detection of the pitch. An additional detector processes the waveform signal to measure a time interval between a pair of the peaks so as to detect a plucking point. A controller controls the tone generator according to the detected plucking point to change the timbre of the tone generator.

    摘要翻译： 在具有手动操作以开始声振动的声学仪器的电子乐器和响应于声振动的乐音发生器产生具有与声音振动相对应的音高的乐音，音调检测装置利用拾音器拾取 提高声音振动，将其转换为波形信号。 此外，第一检测器根据用于处理波形信号的快速算法进行操作，以便响应地产生表示声振动的音调的第一输出，并且第二检测器与第一检测器并联操作，以根据 以缓慢的算法，以便稳定地产生代表声振动的音调的第二输出。 选择器选择性地将第一输出和第二输出中的一个输入到音调发生器，使得第一检测器和第二检测器可以协作以确保对音调的响应和稳定的检测。 附加的检测器处理波形信号以测量一对峰之间的时间间隔，以便检测拔除点。 控制器根据检测到的采摘点控制乐音发生器，以改变乐音发生器的音色。

    Machine Learning to Generate Music from Text
    9.
    发明申请
    Machine Learning to Generate Music from Text 审中-公开

    公开(公告)号：US20180190249A1

    公开(公告)日：2018-07-05

    申请号：US15394895

    申请日：2016-12-30

    申请人： Google Inc.

    发明人： Dominik Roblek ,  Douglas Eck

    IPC分类号： G10H1/00 ,  G06F17/24 ,  G10L25/30 ,  G06F17/27 ,  G06N99/00

    CPC分类号： G10H1/0025 ,  G06F17/241 ,  G06F17/2785 ,  G06N20/00 ,  G10H2210/111 ,  G10H2240/085 ,  G10H2250/311 ,  G10L25/30

    摘要： The present disclosure provides systems and methods that leverage one or more machine-learned models to generate music from text. In particular, a computing system can include a music generation model that is operable to extract one or more structural features from an input text. The one or more structural features can be indicative of a structure associated with the input text. The music generation model can generate a musical composition from the input text based at least in part on the one or more structural features. For example, the music generation model can generate a musical composition that exhibits a musical structure that mimics or otherwise corresponds to the structure associated with the input text. For example, the music generation model can include a machine-learned audio generation model. In such fashion, the systems and methods of the present disclosure can generate music that exhibits a globally consistent theme and/or structure.