A speech-music classification method according to a developed neural system and beat spectrum is proposed achieve accurate of through pre-emphasis, endpoint detection, framing, windowing other steps preprocess collect vocal music signals. After fast Fourier transforms triangle filter processing, the Mel frequency cepstrum coefficient (MFCC) obtained, discrete cosine transform performed obtain s...

In the analysis of musical acoustics, we usually use the power spectrum to describe the difference between timbres from two music instruments. However, according to our experiments, the power spectrum cannot be used as effective features for erhu instrument identification. In this paper, we use MFCC (mel-scale frequency cepstral coefficients) as features for music instrument identification usin...

In this work, following our previous studies, we study and quantify the effect of pitch on LPCC and PLPC features and explore their efficacy for children’s mismatched ASR in comparison to MFCC. Our analysis shows that, unlike MFCC, LPCC feature has no major influence of pitch variations. On the other hand, similar to MFCC, though PLPC is also found to be significantly effected by pitch variatio...

this paper introduces a new method of extracting MFCC for speech recognition and it is compared with the conventional MFCC method. The new algorithm reduces the calculation steps by 53% compared to conventional method. Simulation result indicates the new method has a recognition accuracy of 92.93% only 1.5% less than the conventional MFCC method which is has accuracy of 94.43%. However, the num...

A new feature set for ASR called Rate-Spectrum(RS) is proposed. RS is a spectral representation obtained using a computational auditory model. The feature is noise-robust and considerably speaker invariant. RS matches the smoothed log spectrum both in shape and dynamic range variation. DCT is used to reduce dimensionality. Comparison of the proposed features with MFCC is done using an Isolated ...

Digital Speech Signal Processing is the process of converting one type of speech signal representation to another type of representation so as to uncover various mathematical or practical properties of the speech signal and do appropriate processing to support in solving both fundamental and deep troubles of interest. Digital Speech Processing chain has two different main model They are Speech ...

Yuan cosmos is a virtual world linked and created by scientific technological means, which mapped interacted with the real world, digital living space new social system. With increasing popularity of data acquisition production equipment, people are increasingly convenient to produce multimedia such as images, graphics, audio, video, animation, three-dimensional models. In addition rapid develo...

A person's voice contains various parameters that convey information such as emotion, gender, attitude, health and identity. This report talks about speaker recognition which deals with the subject of identifying a person based on their unique voiceprint present in their speech data. Pre-processing of the speech signal is performed before voice feature extraction. This process ensures the voice...

-Speech emotion recognition is a rapidly growing field of research that aims to automatically identify emotions from speech signals. This paper presents using machine learning techniques. The study begins by providing an overview the various approaches used in recognition, including feature extraction, selection, and classification. These selected features like pitch, MFCC are compared with exi...