Method of noise reduction based on dynamic aspects of speech
First Claim
1. A method for reducing noise in a noisy input signal, the method comprising:
- converting a frame of the noisy input signal into an input feature vector;
obtaining a static-based prediction for a noise-reduced feature vector using a prior model of static aspects of clean signals;
obtaining a dynamic-based prediction for the noise-reduced feature vector using a prior model of dynamic aspects of clean signals;
combining the static-based prediction and the dynamic-based prediction to form at least part of a combined prediction; and
multiplying the combined prediction by a measure of the probability of the input feature vector occurring to produce at least one component of the noise-reduced feature vector.
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Abstract
A system and method are provided that reduce noise in pattern recognition signals. To do this, embodiments of the present invention utilize a prior model of dynamic aspects of clean speech together with one or both of a prior model of static aspects of clean speech, and an acoustic model that indicates the relationship between clean speech, noisy speech and noise. In one embodiment, components of a noise-reduced feature vector are produced by forming a weighted sum of predicted values from the prior model of dynamic aspects of clean speech, the prior model of static aspects of clean speech and the acoustic-environmental model.
34 Citations
25 Claims
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1. A method for reducing noise in a noisy input signal, the method comprising:
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converting a frame of the noisy input signal into an input feature vector;
obtaining a static-based prediction for a noise-reduced feature vector using a prior model of static aspects of clean signals;
obtaining a dynamic-based prediction for the noise-reduced feature vector using a prior model of dynamic aspects of clean signals;
combining the static-based prediction and the dynamic-based prediction to form at least part of a combined prediction; and
multiplying the combined prediction by a measure of the probability of the input feature vector occurring to produce at least one component of the noise-reduced feature vector. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer-readable medium having computer-executable instructions for performing steps comprising:
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using a prior model of static aspects of clean speech to produce a static-based predicted value;
using a prior model of dynamic aspects of clean speech to produce a dynamic-based predicted value;
applying a noisy feature vector representing a frame of noisy speech to an acoustic environment model to produce an acoustic environment-based predicted value; and
combining the static-based predicted value, the dynamic-based predicted value and the acoustic environment-based predicted value to form at least one component of a noise-reduced feature vector. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22)
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23. A method of reducing noise in a noisy speech signal, the method comprising:
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predicting a dynamic-based noise-reduced value using a model of dynamic aspects of speech;
predicting an acoustic environment-based noise-reduced value using a model of an acoustic environment;
combining the dynamic-based noise-reduced value and the acoustic environment-based noise-reduced value to produce at least one component of a noise-reduced portion of the noisy speech signal. - View Dependent Claims (24, 25)
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Specification