Noise suppressing apparatus and its adjusting apparatus

• US 5,335,312 A
• Filed: 09/04/1992
• Issued: 08/02/1994
• Est. Priority Date: 09/06/1991
• Status: Expired due to Fees

• Current Assignee: New Energy and Industrial Technology Development Organizatio
• Original Assignee: Technology Research Association Of Medical And Welfare Apparatus
• Inventors: Takagi, Hideyuki, Mekata, Tsuyoshi
• Primary Examiner(s): Knepper, David D.
• Application Number:
  US07/940,499
• Time in Patent Office: 697 Days
• Field of Search: 395/2, 395/2.11, 395/2.35, 395/2.36, 395/2.41
• US Class Current: 704/202
• CPC Class Codes: G10L 21/0208 Noise filtering
• CPC Class Codes: G10L 25/18 the extracted parameters being spectral information of each sub-band
• CPC Class Codes: G10L 25/30 using neural networks

Abstract

The adjustment of a noise suppressing apparatus inputs the voice signal with the noises being piled up in it to decide the weight coefficient of the neutral network 130 with a back propagating method so that the errors of the output signal and of the noiseless signal may become minimum, the noise suppressing apparatus where noises in a voice signal are suppressed even in a situation where the positional relation between the noise source and the voice source may often change, and noises offensive to the voice after the noise suppression may not remain, the suppressing effect is not deteriorated even if the time pattern of the input signal is varied.

Claims

1. A noise suppressing apparatus comprising:

one channel of voice and additional noise;

frequency band dividing means for dividing an input signal from only said one channel with voice and additional noise into a plurality of frequency bands with each frequency band including a voice component and an additional noise component within the respective frequency band of the input signal;

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the frequency band dividing means, a hidden layer having a plurality of units connected with the input layer units, and an output layer of a single unit connected with the hidden layer units,

wherein output signals with noises being suppressed are obtained from the single unit of the output layer.

2. A noise suppressing apparatus comprising:

one channel of voice and additional noise;

frequency band dividing means for dividing into a plurality of frequency bands an input signal from only said one channel with voice and additional noise with each frequency band including a voice component and an additional noise component within the respective frequency band of the input signal;

wave detecting means for outputting an envelope of each of the frequency bands;

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the wave detecting means, a hidden layer having a plurality of units being connected with the plurality of input layer units, and an output layer composed of units equal in number to the input layer and being connected with the plurality hidden layer units, each unit in the output layer produces an output signal;

means for obtaining a plurality of respective products of the output signals of each output layer by the frequency bands,

means for calculating a total of the plurality of products, wherein the total is outputted as an output signal with noise being suppressed.

3. A noise suppressing apparatus comprising:

one channel with voice and additional noise;

frequency band dividing means for dividing into a plurality of frequency bands an input signal from only said one channel with voice and additional noises with each frequency band including a voice component and an additional noise component within the respective frequency band of the input signal;

wave detecting means for outputting an envelope of each of the frequency bands, the wave detecting means produces a plurality of output signals;

neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the wave detecting means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer having units equal in number to the plurality of input layer units and connected with the plurality hidden layer units,

means for dividing, for each frequency band, the output signal of the output layer units by the output signal of the wave detecting means, and producing outputs;

means for calculating a product of the outputs of the means for dividing by the frequency bands,

means for calculating a total of all the products, wherein the total is outputted as an output signal with the noises being suppressed.

4. An adjusting method of a noise suppressing apparatus including a noiseless sound signal generating means for generating noiseless sound signals, a noise addition means for adding the noises on the noiseless sound signals, a first frequency band dividing means the same in construction as the noise suppressing apparatus described in the claim 3 with the output signal of the noise addition means being an input signal, a first wave detecting means and a neural network, a second frequency band dividing means for dividing into a plurality of frequency bands the noiseless sound signal, a second wave detecting means for outputting the envelope of the respective output signals of each of the second frequency band dividing means, a weight coefficient renewing means for renewing the weight coefficients of the neural network with a back propagating method so that the average difference between the output signal of the neutral network and the teacher signal may become smaller with the output signal of the second wave detecting means being made a teacher signal input, an error computing means for calculating, outputting the average error between the output signal of the above described second wave detecting means and the output signal of the first wave detecting means, an adjustment completion judging means for suspending the operation of the weight coefficient renewing means when the computed error has been lower than the set threshold value or when the reduction in the error has been focused, comprising the steps of

repeating, to the judgment of the adjustment completion by the adjustment completion judging means, of

generating of the noiseless sound signal by the noiseless sound signal source,

adding the noises onto the noiseless sound signal by the noise addition means,

calculating by the respective frequency band dividing means, the wave detecting means, the neutral network, and the multiplying mean,

calculating of the error by the error calculating means,

judging by the adjustment completion judging means,

renewing of the weight coefficient by the weight coefficient renewing means so as to make the weight coefficient of the neutral network optimum at the adjustment completion.

5. A noise suppressing apparatus comprising:

a plurality of microphones for producing time signals; and

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units for receiving time signals from the plurality of microphones, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer of single unit connected with the hidden layer units,

wherein an output signal whose noises are suppressed is obtained from the single unit of the output layer.

6. A noise suppressing apparatus comprising:

a plurality of microphones which produce outputs,

wave detecting means for outputting an envelope of each output signal of the microphones, the wave detecting means producing a plurality of outputs;

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the wave detecting means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer having units equal in number to the plurality of input layer units and connected with the plurality of hidden layer units,

means for calculating, for each of the microphones, a product of the output signals of the neural network by the output signals of the wave detecting means,

means for calculating a total of the products, wherein the total is outputted as a signal whose noises are suppressed.

7. A noise suppressing apparatus comprising:

a plurality of microphones which product output signals,

wave detecting means for outputting an envelope of each output signal of the microphones, the wave detecting means producing a plurality of outputs;

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the wave detecting means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer having units equal in number to the plurality of input layer units and connected with the plurality of hidden layer units,

means for dividing, for each of corresponding signals, by the output signals of the wave detecting means, the output signals of the neural network,

means for calculating a product of each result of the division by the output signal of the wave detecting means,

means for calculating a total of the products, wherein the total is outputted as an output signal whose noises are suppressed.

8. A noise suppressing apparatus comprising:

a plurality of microphones,

a frequency band dividing means connected with the microphones, the frequency band dividing means producing a plurality of output signals;

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the output terminals of the frequency band dividing means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer of a single unit connected with the hidden layer units,

wherein output signals in which noises are suppressed are output by the single unit of the output layer.

9. A noise suppressing apparatus comprising:

a plurality of microphones,

a plurality of frequency band dividing means connected respectively with the microphones and producing output signals,

wave detecting means, having a plurality of output signals, for outputting an envelope of each output signal of the frequency band dividing means,

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the wave detecting means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer having units equal in number to the plurality of input layer units and connected with the plurality of hidden layer units,

means for obtaining, for each of the frequency bands, a product of the output signals of the neural network by the output signals of the frequency band dividing means,

means for calculating a total of the products, wherein the total is outputted as an output signal whose noises are suppressed.

10. A noise suppressing apparatus comprising:

a plurality of microphones,

a plurality of frequency band dividing means connected with the microphones and for producing output signals,

a plurality of wave detecting means equal in number to the plurality of frequency band dividing means,

a neural network, having weight coefficients to emphasize voice and suppress noise, including an input layer having a plurality of units connected with the plurality of wave detecting means, a hidden layer having a plurality of units connected with the plurality of input layer units, and an output layer having units equal in number to the plurality of input layer units and connected with the plurality of hidden layer units,

means for dividing by each output signal of the wave detecting means, the output signals of the neural network,

means for calculating a product of the results of the division by the output signals of the plurality of frequency band dividing means,

means for calculating a total of the products, wherein the total is outputted as an output signal whose noises are suppressed.

11. An adjusting method of a noise suppressing apparatus including noise sources and noiseless sound signal sources disposed as in the actual use circumference, a means for extracting only the signals of the noiseless sound signal sources, a noise suppressing apparatus described in one of the claims 5, 6, 7, 8, 9, 10, a weight coefficient renewing means for renewing the weight coefficients of the neural network having the noise suppressing apparatus with a back propagation method so that the average difference between the output signal of the noise suppressing apparatus and the teacher signal may become smaller, with the output signal of the noiseless sound signal generating means being provided as the teacher signal input, an error computing means for calculating and outputting the average error between the output signal of the noise suppressing apparatus and the output signal of the noiseless sound signal extracting means, an adjustment completion judging means for suspending the operation of the weight coefficient renewing means when the computed error has been lower than the set threshold value or when a reduction in the error has been focused, comprising the steps, to the judgment of the adjustment completion by the adjustment completion judging means,

generating of the signals by the noiseless sound sources,

processing of the signals by the noise suppressing means,

calculating of the error by the error computing means,

judging by the adjustment completion judging means,

renewing of the weight coefficient by the weight coefficient renewing means so as to make optimum the weight coefficients of the neural network at the adjustment completion.

12. An adjusting method of a noise suppressing apparatus including a noiseless sound signal generating means for generating noiseless sound signals, a noise addition means for adding the noises on the noiseless sound signals, a first frequency band dividing means with the output signal of the noise addition means being input signal, a first wave detecting means and a neutral network, a second frequency band dividing means for dividing into a plurality of frequency bands the noiseless sound signal, a second wave detecting means for outputting an envelope of the respective output signals of each of the second frequency band dividing means signals, a weight coefficient renewing means for renewing the weight coefficients of the neural network with a back propagating method so that the average difference between the output signal of the neutral network and the teacher signal may become smaller with the output signal of the second wave detecting means being provided as the teacher signal input, an error computing means for calculating and outputting the average error between the output signal of the second wave detecting means and the output signal of the first wave detecting means, an adjustment completion judging means for suspending the operation of the weight coefficient renewing means when the computed error has been lower than the set threshold value or when the reduction in the error has been focused, comprising the steps of

repeating, to a judgment of the adjustment completion by the adjustment completion judging means,

generating of the noiseless sound signal by the noiseless sound signal source,

piling up of noises onto the noiseless sound signal by the noise addition means,

processing by the frequency band dividing means, the wave detecting means, and the neutral network,

calculating of the error by the error calculating means,

judging by the adjustment completion judging means,

renewing of the weight coefficient by the weight coefficient renewing means so as to make optimum the weight coefficients of the neural network at the adjustment completion.

13. A noise suppressing apparatus comprising:

means for calculating spectrum of input signal;

a feed forward neural network, having weighting coefficients which emphasize voice and suppress noise, having at least three layers including an input layer having a plurality of units which are inputted magnitude of each frequency spectrum value;

a hidden layer having a plurality of units connected with the plurality of input layer units;

an output layer having units equal in number to the input layer units connected with the plurality of hidden layer units and producing an output;

means for multiplying the respective spectrum and the output of the output layer of the neural network; and

means for calculating time region signal from the output of the means for multiplying, wherein the output signal of the means for calculating time region signal is outputted as an output signal.

14. A noise suppressing apparatus comprising:

means for calculating spectrum of an input signal;

a feed forward neural network, having weighting coefficients which emphasize voice and suppress noise, with at least three layers including an input layer having a plurality of units which are inputted each frequency spectrum value calculated by means for calculating spectrum;

a hidden layer having a plurality of units connected with the plurality of input layer units;

an output layer having units equal in number to the input layer units and connected with the plurality of hidden layer units; and

means for calculating time region signals from spectrum using data from the output layer of the neural network;

wherein the output signal of the means for calculating time region signal is outputted as an output signal.