利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

98 条记录 (耗时 0.033 秒)

    Speech & Music Discriminator for Multi-Media Application
    3.
    发明申请
    Speech & Music Discriminator for Multi-Media Application 失效
    多媒体应用程序的语音和音乐鉴别器

    公开(公告)号：US20110029308A1

    公开(公告)日：2011-02-03

    申请号：US12813350

    申请日：2010-06-10

    申请人： Alon Konchitsky ,  Alberto D. Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    发明人： Alon Konchitsky ,  Alberto D. Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    IPC分类号： G10L15/00

    CPC分类号： G10L25/78

    摘要： The present invention relates to means and methods of classifying speech and music signals in voice communication systems, devices, telephones, and methods, and more specifically, to systems, devices, and methods that automate control when either speech or music is detected over communication links. The present invention provides a novel system and method for monitoring the audio signal, analyze selected audio signal components, compare the results of analysis with a pre-determined threshold value, and classify the audio signal either as speech or music.

    摘要翻译： 本发明涉及在语音通信系统，设备，电话和方法中分类语音和音乐信号的方法和方法，更具体地说，涉及当通过通信链路检测到语音或音乐时自动化控制的系统，设备和方法 。 本发明提供了一种用于监视音频信号，分析所选择的音频信号分量，将分析结果与预定阈值进行比较并将音频信号分类为语音或音乐的新型系统和方法。

    Method for Wind Noise Reduction
    6.
    发明申请
    Method for Wind Noise Reduction 失效
    降噪风险的方法

    公开(公告)号：US20110004470A1

    公开(公告)日：2011-01-06

    申请号：US12795188

    申请日：2010-06-07

    申请人： Alon Konchitsky ,  Alberto D. Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    发明人： Alon Konchitsky ,  Alberto D. Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    IPC分类号： G10L21/02

    CPC分类号： G10L21/0208

    摘要： A noisy signal is picked up by a microphone, digitized by an Analog to Digital Converter and fed to a processor for analysis and wind noise reduction. Most of noise reduction methods are based on the assumption that the interfering noise is stationary or slowly varying compared with speech. This assumption allows “learning” the characteristics of the noise between speech pauses and, based on a noise estimate, to build different filters that reduce the noise. In the case of wind noise this basic assumption is not valid. Wind noise is highly non-stationary, its power and spectral characteristics vary greatly. Because wind noise is not stationary, regular noise reduction methods cannot be used to reduce wind noise. For reducing wind noise effects in a device, the presence of wind should be detected reliably and then a novel approach presented here must be applied to eliminate the wind noise.

    摘要翻译： 噪声信号由麦克风拾取，由模数转换器数字化，并馈送到处理器进行分析和减少风噪声。 大多数降噪方法是基于干扰噪声与语音相比是静止的或缓慢变化的假设。 该假设允许“学习”语音暂停之间的噪声的特性，并且基于噪声估计来建立减少噪声的不同滤波器。 在风噪声的情况下，这个基本假设是无效的。 风噪声非常不稳定，其功率和光谱特性差异很大。 由于风噪声不稳定，因此不能采用常规的降噪方法来减少风噪声。 为了减少设备中的风噪声影响，应该可靠地检测风的存在，然后必须采用这里提出的新颖方法来消除风噪声。

    Method for wind noise reduction
    7.
    发明授权
    Method for wind noise reduction 失效
    减少风噪声的方法

    公开(公告)号：US08433564B2

    公开(公告)日：2013-04-30

    申请号：US12795188

    申请日：2010-06-07

    申请人： Alon Konchitsky ,  Alberto D Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    发明人： Alon Konchitsky ,  Alberto D Berstein ,  Sandeep Kulakcherla ,  William Martin Ribble ,  Kevin Fitzgerald ,  Don Seferovich

    IPC分类号： G10L19/00 ,  G10L19/14 ,  G10L21/02

    CPC分类号： G10L21/0208

    摘要： A noisy signal is picked up by a microphone, digitized by an Analog to Digital Converter and fed to a processor for analysis and wind noise reduction. Most of noise reduction methods are based on the assumption that the interfering noise is stationary or slowly varying compared with speech. This assumption allows “learning” the characteristics of the noise between speech pauses and, based on a noise estimate, to build different filters that reduce the noise. In the case of wind noise this basic assumption is not valid. Wind noise is highly non-stationary, its power and spectral characteristics vary greatly. Because wind noise is not stationary, regular noise reduction methods cannot be used to reduce wind noise. For reducing wind noise effects in a device, the presence of wind should be detected reliably and then a novel approach presented here must be applied to eliminate the wind noise.

    摘要翻译： 噪声信号由麦克风拾取，由模数转换器数字化，并馈送到处理器进行分析和减少风噪声。 大多数降噪方法是基于干扰噪声与语音相比是静止的或缓慢变化的假设。 该假设允许“学习”语音暂停之间的噪声的特性，并且基于噪声估计来建立减少噪声的不同滤波器。 在风噪声的情况下，这个基本假设是无效的。 风噪声非常不稳定，其功率和光谱特性差异很大。 由于风噪声不稳定，因此不能采用常规的降噪方法来减少风噪声。 为了减少设备中的风噪声影响，应该可靠地检测风的存在，然后必须采用这里提出的新颖方法来消除风噪声。