In this paper, an algorithm for detecting and attenuating puff noises frequently generated under the mobile environment is proposed. As a baseline system, puff detection system is designed based on Gaussian Mixture Model (GMM), and 39th Mel Frequency Cepstral Coefficient (MFCC) is extracted as feature parameters. To improve the detection performance, effective acoustic features for puff detecti...

A new cepstrum-based channel compensation method is proposed for speaker verification over the telephone network. The method consists of intra-frame and interframe cepstral processing. For the former, a poleremoved cepstrum is derived, where the LP poles with frequency higher than a certain threshold are removed. For the latter, we introduce a novel way of cepstral mean subtraction called diffe...

Speaker recognition is the identification of the person who is speaking by characteristics of their voices, also called “voice recognition”. The components of Speaker Recognition includes Speaker Identification(SI) and Speaker Verification(SV). Speaker identification is the task of determining an unknown speakers identity. If the speaker claims to be of a certain identity and the voice is to ve...

A major challenge for automatic speech recognition (ASR) relates to significant performance reduction in noisy environments. Recently, the study of the emotional content of speech signals got more importance and hence, many systems have been proposed to identify the emotional content of a spoken utterance. The important aspects of the design of a speech emotion recognition system are pre-proces...

In this paper, we propose several compensation approaches to alleviate the effect of additive noise on speech features for speech recognition. These approaches are simple yet efficient noise reduction techniques that use online constructed pseudo stereo codebooks to evaluate the statistics in both clean and noisy environments. The process yields transforms for noise-corrupted speech features to...

A method based on cepstral deconvolution technique is proposed for measurement of absorption and scattering coefficients of materials. The reverberation room method standardized by International Organization for Standardization (ISO) is taken as the reference for measurements. Several measurements are conducted in a physically scaled reverberation room and results are evaluated by these two met...

This work presents a noise spectrum estimator based on the Gaussian mixture model (GMM)-based speech presence probability (SPP) for robust speech recognition. Estimated noise spectrum is then used to compute a subband a posteriori signal-to-noise ratio (SNR). A sigmoid shape weighting rule is formed based on this subband a posteriori SNR to enhance the speech spectrum in the auditory domain, wh...

Automatic speech recognition by machine is one of the most efficient methods for man-machine communications. Because speech waveform is nonlinear and variant. Speech recognition requires a lot of intelligence and fault tolerance in the pattern recognition algorithms. Accurate vowel recognition forms the backbone of most successful speech recognition systems. A collection of techniques exists to...

Recent studies have reported that the performance of Automatic Speech Recognition (ASR) technologies designed for normal speech notably deteriorates when it is evaluated by whispered speech. Therefore, detection useful in order to attenuate mismatch between training and testing situations. This paper proposes two new Glottal Flow (GF)-based features, namely, GF-based Mel-Frequency Cepstral Coef...

In this paper, a gammatone-domain model combination method is proposed for consonant recognition in noisy environments. For this task, we first define a gammatone cepstral coefficient (GCC) as the cepstral representation of the averaged envelopes of a gammatone filtered signal. Then, we investigate a proper phonetic unit by comparing monophone, diphone, and triphone acoustic models, where it is...