On Dynamic Pitch Benefit for Speech Recognition in Speech Masker

Automatic Speech Recognition using Pitch Information in Dynamic Bayesian Networks

the effects of speech rate,prosodic features, and blurred speech on iranian efl learners listening comprehension

کلید واژه ها به زبان انگلیسی: effect of speech rate on listening comprehension, blurred speech,segmental and suprasegmental features,authentic speech,intelligibility, discrimination, omission, assimilation چکیده: سرعت مطالب شنیداری در کلام پیوسته بطور کلی همواره کابوسی بوده برای یادگیرنده های زبان دوم و بالاخص برای شنوندگان ایرانی. علی رغم عقل سلیم که کلام با سرعت کندتری فعالیتهای درک مطلب شن...

Improving the performance of MFCC for Persian robust speech recognition

The Mel Frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. In this paper to achieve a satisfactorily performance in Automatic Speech Recognition (ASR) applications we introduce a noise robust new set of MFCC vector estimated through following steps. First, spectral mean normalization is a pre-processing which applies to t...

Intelligibility predictions for speech against fluctuating masker

The effect of masking due to fluctuating sources on speech intelligibility is a phenomenon difficult to predict. Intelligibility scores vary with the efficiency of the energetic masking while the linguistic content of the message and listener’s cognitive performances add to the general incertitude that peaks for the case of masking speech. The present contribution proposes a signal-based assess...

Pitch in Emotional Speech and Emotional Speech Recognition Using Pitch Frequency

The variations of speech parameters due to emotion or stress are noticeable. In the presence of such variations, if a neutral model is used for the system, the speech recognition accuracy deteriorates. The evaluation of how emotion influences speech parameters is the first step towards emotional speech recognition. Pitch frequency is an important parameter in speech processing systems. Therefor...