| 摘要 |
Characterizing an acoustic signal includes extracting a vector from the acoustic signal, where the vector contains information about the nuisance characteristics present in the acoustic signal, and computing a set of likelihoods of the vector for a plurality of classes that model a plurality of nuisance characteristics. Training a system to characterize an acoustic signal includes obtaining training data, the training data comprising a plurality of acoustic signals, where each of the plurality of acoustic signals is associated with one of a plurality of classes that indicates a presence of a specific type of nuisance characteristic, transforming each of the plurality of acoustic signals into a vector that summarizes information about the acoustic characteristics of the signal, to produce a plurality of vectors, and labeling each of the plurality of vectors with one of the plurality of classes. |
