M. Shahidur Rahman

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This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of(More)
A pitch determination method based on AMDF (Average Magnitude Difference Function) is proposed in this paper. The AMDF is often used to determine the pitch parameter in real-time speech processing applications. Falling trend of AMDF at higher lags, however, makes the method vulnerable to octave errors (pitch doubling or halving). In this paper, we propose(More)
This paper investigates the pitch characteristics of bone conducted speech. Pitch determination of speech signal can not attain the expected level of accuracy in adverse conditions. Bone conducted speech is robust to ambient noise and it has regular harmonic structure in the lower spectral region. These two properties make it very suitable for pitch(More)
This paper proposes a technique for suppressing low-frequency band noise from speech signal. In practice, speech is often corrupted by color noise like car and multi-talker babble noise that affect mostly the low-frequency region of speech signal. We propose a straightforward approach for noise reduction by utilizing bone conducted (BC) speech. Lower(More)
This paper proposes a pitch determination method utilizing the autocorrelation function in the spectral domain. The autocorrelation function is a popular measurement in estimating pitch in time domain. The performance of the method, however, is effected due to the position of dominant harmonics (usually the first formant) and the presence of spurious peaks(More)
This paper presents methodologies involved in diphone preparation for Bangla text to speech synthesis. A concatenation based synthesis system comprises basically two modules- one is natural language processing and other is digital signal processing (DSP). Natural language processing implies converting text to its pronounceable text, called text(More)
The conventional model of the linear prediction analysis suffers from difficulties in estimating vocal tract characteristics of high-pitched speakers. This paper shows that for voiced speech the vocal tract characteristics can be estimated accurately by homomorphic deconvolution in the autocorrelation domain. The speech autocorrelation function used by(More)
A new system identification based method has been proposed for accurate estimation of vocal tract parameters. An often encountered problem in using the conventional linear prediction analysis is due to the harmonic structure of the excitation source of voiced speech. This harmonic characteristic is coupled with the estimation of autoregressive (AR)(More)
This work attempts to find the most optimal setting for shallow artificial neural network (ANN) for Bengali digit dataset. Recognition of handwritten Bengali numerals has recently gained much interest among researchers due to significant performance gain found in the recognition of English numerals using artificial neural network. In this work, a new(More)