ENHANCEMENT OF ALARYNGEAL SPEECH UTILIZING SPECTRAL SUBTRACTION AND MINIMUM STATISTICS
This paper proposes improvements to the electrolarynx device, which allows a patient to speak after the larynx is removed. Speech through existing electrolarynx devices is corrupted by high levels of noise and sounds unnatural. The proposed algorithm is based upon spectral subtraction techniques and modifies the magnitude of the speech signal in the frequency domain. Here, with the introduction of Discrete Cosine Transform (DCT) domain analysis using minimum statistics, the proposed algorithm effectively reduces high levels of noise generated by the electrolarynx. Unlike existing methods, the proposed algorithm docs not require the use of a voice activity detector and the Discrete Cosine Transform domain is more proficient at isolating speech signal energy. The new algorithm presented in this paper is readily adaptable to hardware implementation and has the potential to be included in a handheld electrolarynx device in the future.
Spectral subtraction speech enhancement alaryngeal speech electrolarynz minimum statistics cosine transforms dct
RAONAAK KABIR AARON GREENBLATT KAREN PANETTA SOS AGAIAN
Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts, 02155, Department of Electrical Engineering, University of Texas/San Antonio, San Antonio, Texas 78249-0669
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
3704-3709
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）