DATA AUGMENTATION SYSTEM AND METHOD FOR MULTI-MICROPHONE SYSTEMS
A method, computer program product, and computing system for obtaining one or more speech signals from a first device, thus defining one or more first device speech signals. One or more speech signals may be obtained from a second device, thus defining one or more second device speech signals. One or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals may be generated. One or more augmented second device speech signals may be generated based upon, at least in part, the one or more noise component models and first device training data.
1 . A computer-implemented method, executed on a computing device, comprising:
obtaining one or more speech signals from a first device, thus defining one or more first device speech signals;
obtaining one or more speech signals from a second device, thus defining one or more second device speech signals;
generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals; and
generating one or more augmented second device speech signals based upon, at least in part, the one or more noise component models and first device training data.
2 . The computer-implemented method of claim 1 , further comprising:
processing the one or more first device speech signals; and
processing the one or more second device speech signals.
3 . The computer-implemented method of claim 2 , wherein processing the one or more first device speech signals includes:
detecting one or more speech active portions from the one or more first device speech signals; and
identifying one or more noise components within the one or more first device speech signals.
4 . The computer-implemented method of claim 2 , wherein processing the one or more second device speech signals includes:
detecting one or more speech active portions from the one or more second device speech signals; and
identifying one or more noise components within the one or more second device speech signals.
5 . The computer-implemented method of claim 1 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating one or more time-frequency gain functions mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals.
6 . The computer-implemented method of claim 1 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating a noise component model with only noise components from the one or more second device speech signals.
7 . The computer-implemented method of claim 1 , further comprising:
adding the one or more noise component models to a codebook of noise component models.
8 . A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:
obtaining one or more speech signals from a first device, thus defining one or more first device speech signals;
obtaining one or more speech signals from a second device, thus defining one or more second device speech signals;
generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals; and
generating one or more augmented second device speech signals based upon, at least in part, the one or more noise component models and first device training data.
9 . The computer program product of claim 8 , wherein the operations further comprise:
processing the one or more first device speech signals; and
processing the one or more second device speech signals.
10 . The computer program product of claim 9 , wherein processing the one or more first device speech signals includes:
detecting one or more speech active portions from the one or more first device speech signals; and
identifying one or more noise components within the one or more first device speech signals.
11 . The computer program product of claim 9 , wherein processing the one or more second device speech signals includes:
detecting one or more speech active portions from the one or more second device speech signals; and
identifying one or more noise components within the one or more second device speech signals.
12 . The computer program product of claim 8 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating one or more time-frequency gain functions mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals.
13 . The computer program product of claim 8 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating a noise component model with only noise components from the one or more second device speech signals.
14 . The computer program product of claim 8 , wherein the operations further comprise:
adding the one or more noise component models to a codebook of noise component models.
15 . A computing system comprising:
a memory; and
a processor configured to obtain one or more speech signals from a first device, thus defining one or more first device speech signals, wherein the processor is further configured to obtain one or more speech signals from a second device, thus defining one or more second device speech signals, wherein the processor is further configured to generate one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals, and wherein the processor is further configured to generate one or more augmented second device speech signals based upon, at least in part, the one or more noise component models and first device training data.
16 . The computing system of claim 15 , wherein the processor is further configured to:
process the one or more first device speech signals; and
process the one or more second device speech signals.
17 . The computing system of claim 16 , wherein processing the one or more first device speech signals includes:
detecting one or more speech active portions from the one or more first device speech signals; and
identifying one or more noise components within the one or more first device speech signals.
18 . The computing system of claim 15 , wherein processing the one or more second device speech signals includes:
detecting one or more speech active portions from the one or more second device speech signals; and
identifying one or more noise components within the one or more second device speech signals.
19 . The computing system of claim 15 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating one or more time-frequency gain functions mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals.
20 . The computing system of claim 15 , wherein generating one or more noise component models mapping one or more noise components from the one or more first device speech signals to the one or more second device speech signals includes generating a noise component model with only noise components from the one or more second device speech signals.