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Comparison of Speech Enhancement Algorithms
| Content Provider | Scilit |
|---|---|
| Author | Loizou, Philipos C. |
| Copyright Year | 2013 |
| Description | So far, we have assumed that an estimate of the noise spectrum is available. Such an estimate is critical for the performance of speech-enhancement algorithms as it is needed, for instance, to evaluate the Wiener lter in the Wiener algorithms or to estimate the a priori SNR in the MMSE algorithms or to estimate the noise covariance matrix in the subspace algorithms. The noise estimate can have a major impact on the quality of the enhanced signal. If the noise estimate is too low, annoying residual noise will be audible, and if the noise estimate is too high, speech will be distorted, possibly resulting in intelligibility loss. The simplest approach is to estimate and update the noise spectrum during the silent (e.g., during pauses) segments of the signal using a voice activity detection (VAD) algorithm. Although such an approach might work satisfactorily in stationary noise (e.g., white noise), it will not work well in more realistic environments (e.g., in a restaurant), wherein the spectral characteristics of the noise change constantly. This chapter focuses on a new class of algorithms that estimate the noise continuously, even during speech activity. As such, these algorithms are suitable for highly nonstationary noisy environments. Book Name: Speech Enhancement |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2011-0-16639-5&isbn=9780429096181&doi=10.1201/b14529-15&format=pdf |
| Ending Page | 579 |
| Page Count | 1 |
| Starting Page | 579 |
| DOI | 10.1201/b14529-15 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2013-02-25 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Speech Enhancement Audiology and Language Speech Enhancement Noise Spectrum Wiener Noise Estimate Enhancement Algorithms Algorithms Or To Estimate |
| Content Type | Text |
| Resource Type | Chapter |
