| 摘要 |
A system and method are provided for processing audio and speech signals using a pitch and voicing dependent spectral estimation algorithm (voicing algorithm) to accurately represent voiced speech, unvoiced speech, and mixed speech in the presence of background noise, and background noise with a single model. The present invention also modifies the synthesis model based on an estimate of the current input signal to improve the perceptual quality of the speech and background noise under a variety of input conditions. The present invention also improves the voicing dependent spectral estimation algorithm robustness by introducing the use of a Multi-Layer Neural Network in the estimation process. The voicing dependent spectral estimation algorithm provides an accurate and robust estimate of the voicing probability under a variety of background noise conditions. This is essential to providing high quality intelligible speech in the presence of background noise. In one embodiment, the waveform coding is implemented by separating the input signal into at least two sub-band signals and encoding one of the at least two sub-band signals using a first encoding algorithm to produce at least one encoded output signal; and encoding another of said at least two sub-band signals using a second encoding algorithm to produce at least one other encoded output signal, where the first encoding algorithm is different from the second encoding algorithm. In accordance with the described embodiment, the present invention provides an encoder that codes N user defined sub-band signal in the baseband with one of a plurality of waveform coding algorithms, and encodes N user defined sub-band signals with one of a plurality of parametric coding algorithms. That is, the selected waveform/parametric encoding algorithm may be different in each sub-band.
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