Searched for: subject%3A%22RTF%255C+estimation%22
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document
Li, C. (author), Martinez, Jorge (author), Hendriks, R.C. (author)
Estimation of the acoustic-scene related parameters such as relative transfer functions (RTFs) from source to microphones, source power spectral densities (PSDs) and PSDs of the late reverberation is essential and also challenging. Existing maximum likelihood estimators typically consider only subsets of these parameters and use each time frame...
journal article 2023
document
Li, C. (author), Hendriks, R.C. (author)
Estimating the parameters that describe the acoustic scene is very important for many microphone array applications. For example, consider the power spectral densities (PSDs) or relative acoustic transfer functions (RTFs) that are required when estimating a particular sound source using multi-microphone noise reduction. State-of-the-art...
conference paper 2023
document
Li, C. (author), Hendriks, R.C. (author)
Spatial filtering techniques typically rely on estimates of the target relative transfer function (RTF). However, the target speech signal is typically corrupted by late reverberation and ambient noise, which complicates RTF estimation. Existing methods subtract the noise covariance matrix to obtain the target plus late reverberation covariance...
conference paper 2023
document
Li, C. (author), Martinez, Jorge (author), Hendriks, R.C. (author)
Many multi-microphone algorithms depend on knowing the relative acoustic transfer functions (RTFs) of the individual sound sources in the acoustic scene. However, accurate joint RTF estimation for multiple sources is a challenging problem. Existing methods to jointly estimate the RTF for multiple sources have either no satisfying performance, or...
conference paper 2022
Searched for: subject%3A%22RTF%255C+estimation%22
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