Using Monte Carlo dropout for non-stationary noise reduction from speech.
Nazreen P. M.A. G. RamakrishnanPublished in: CoRR (2018)
Keyphrases
- non stationary
- monte carlo
- noise reduction
- speech enhancement
- speech signal
- noisy environments
- signal to noise ratio
- monte carlo simulation
- speech recognition
- edge detection
- markov chain
- vocal tract
- importance sampling
- automatic speech recognition
- adaptive algorithms
- noise level
- linear prediction
- autoregressive
- monte carlo methods
- speech synthesis
- monte carlo tree search
- markovian decision
- white noise
- particle filter
- concept drift
- empirical mode decomposition
- text to speech
- adaptive sampling
- matrix inversion
- hearing aids
- machine learning
- variance reduction
- image denoising
- camera motion
- denoising
- image segmentation
- computer vision