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Among conservative treatment methods, speech aid prosthesis combined with speech therapy is widely used method.
In both SS-based and GSS-based dereverberation methods, speech signals from two microphones were used to estimate blindly the compensation parameters for the power SS and GSS (that is, the spectra of the channel impulse responses), and then reverberation was suppressed by SS and the spectrum of dereverberant speech was inverted into a time domain.
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Firstly, in our proposed method, speech synthesized by HMMSS is converted to the natural speech by using a large parallel dictionary previously built in the training stage without using any actual reference speech in the conversion stage.
In this paper, we studied two methods for speech dereverberation for both speech enhancement and ASR tasks.
Spectral restoration methods for speech enhancement aim to remove noise components in noisy speech signals by using a gain function in the spectral domain.
Spectral Subtraction (SS) method is one method for speech enhancement or noise cancellation.
The government should never be used to suppress new and creative – not to mention, effective – methods of speech and expression.
However, compared with these two methods, the speech intelligibility was further improved by the proposed method.
This suggests that the methods for speech emotion recognition can be transferred to singing emotion recognition.
TDOA- (time difference of arrival-) based algorithms are common methods for speech source localization.
In this paper, we continue the research into methods for speech enhancement based on linear filtering.
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