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    • 2. 发明授权
    • Audio amplitude unwrapping
    • US10529354B1
    • 2020-01-07
    • US16115676
    • 2018-08-29
    • Cedar Audio Ltd
    • David Betts
    • G10L21/0208G10L21/038
    • A computer-implemented method for restoring a wrapped audio signal comprising a plurality of digitised signal samples at respective sample times, the method comprising: estimating a sequence of corrections comprising a sequence of numerical values the estimating comprising, for each signal sample: applying, at the sample time, a numerical filter to each of a set of potential corrections to determine a filtered value associated with each set of potential integer corrections wherein the filter enhances the filtered value at sample times when a change in a degree of wrapping occurs relative to sample times when a change in degree of wrapping does not occur; determining a cumulative objective over a plurality of signal samples by accumulating objective values and determining a sequence by selecting for each sample time a correction from the set of potential corrections wherein the correction for each sample time are selected to optimise the cumulative objective.
    • 3. 发明授权
    • Restoring audio signals with mask and latent variables
    • 使用掩码和潜在变量恢复音频信号
    • US09576583B1
    • 2017-02-21
    • US14557014
    • 2014-12-01
    • David Anthony Betts
    • David Anthony Betts
    • G10L21/02G10L21/0216G10L21/0264G10L19/00
    • G10L21/0232G10L21/0264
    • We describe techniques for restoring an audio signal. In embodiments these employ masked positive semi-definite tensor factorization to process the signal in the time-frequency domain. Broadly speaking the methods estimate latent variables which factorize a tensor representation of the (unknown) variance/covariance of an input audio signal, using a mask so that the audio signal is separated into desired and undesired audio source components. In embodiments a masked positive semi-definite tensor factorization of ψftk=MftkUfkVtk is performed, where M defines the mask and U, V the latent variables. A restored audio signal is then constructed by modifying the input signal to better match the variance/covariance of the desired components.
    • 我们描述恢复音频信号的技术。 在实施例中,这些采用掩蔽的正半定标张分解法处理时频域中的信号。 概括地说,这些方法估计潜在变量,其使用掩码将因子分解成期望和不期望的音频源分量的音频信号的(未知)方差/协方差的张量表示因子化。 在实施例中,执行ψftk= MftkUfkVtk的掩蔽的正半定量张量因子分解,其中M定义掩模,U,V为潜变量。 然后通过修改输入信号以更好地匹配所需组件的方差/协方差来构建恢复的音频信号。