Speech Processing Using Mel Frequency Cepstral...

Speaker reognition using Mel Frequency Cepstral Coefficients(MFCC) Abstract Speech processing has emerged as one of the most important application area of digital signal processing. Various fields for research in speech processing are speech recognition, speaker recognition, speech analysis, speech synthesis, speech coding etc. The objective of automatic speaker recognition is to extract, characterize the discriminant features and recognize the information about speaker identity. In this paper we present a voice recognition system based on Mel Frequency Cepstral Coefficients (MFCC) and vector Quantization (VQ). This technique has an advantage that it creates fingerprint of human voice by exploiting human acoustic system and cepstral analysis. MFCC is widely accepted as a baseline for voice recognition due to these unique features. KeywordsMFCC, Vector Quantization, Speaker recognition, Feature extraction, Fast Fourier Transform Introduction Human speech is the most natural form of communication and conveys both meaning and identity. The identity of a speaker can be determined from the information contained in the speech signal through speaker identiï ¬ cation. Speaker identiï ¬ cation is concerned with identifying unknown speakers from a database of speaker models previously enrolled in the system. Speaker (voice) identification has varied applications ranging from opening doors to security systems. Speech processing is widely divided into 5 differentShow MoreRelatedSwot Analysis : Biometrics Biometric Fingerprint And Voice Recognition, Authentication, And Authentication1639 Words   |  7 PagesAbstract— Biometrics is the technique of using exclusive, non moveable, physical characteristics, such as fingerprints, to earn entry for personal identification. Since After the invention of the exclusive technology it has been being used in safety systems and authentication. Presently, security fields have three different types of authentication, they are: Something we know: a password, PIN, or piece of personal information something we have: a card key, smart card, or token and something we are:Read MoreCognitive Signal Processing : Feature Estimation1955 Words   |  8 PagesBehavioural Signal Processing: Feature Estimation in Speech Abstract Human behaviour interrelates closely with the human beings’ mental state. The behavioural information reflects communication, social interaction and even personality. To build a bridge to the human mind over engineering advances, an operational method, Behavioural Signal Processing (BSP) technology, has been introduced, which aims to analyse speech-based human behaviour. The main task of this project is the feature estimationRead MoreClassifiers For Emotional Speech Recognition1670 Words   |  7 PagesComparative Study on Support Vector Machines Classifiers for Emotional Speech Recognition Jimmy Dani Abstract—Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been pro- posed to identify the emotional content of a spoken utterance. There are various important aspects of emotion recognition using speech. The first one is the choice of suitable features for speech representation. The second issue is the design of an appropriateRead MoreSample Extraction Technique Is Necessary For Various Other Form Of The Latest Speech And Speaker Recognition System Essay1986 Words   |  8 PagesMel cepstral feature extraction technique is required in some or the other form in most of the latest speech and speaker recognition system. Here, first samples of speech are splitted into overlapping frames. Generally the length of frame is 25 ms and frame rate is 10 ms. Each and every frames are refined by pre-emphasis filter which amplifies higher frequencies. Next is to apply windowing so that Fourier spectrum for each windowing frame is achieved here Hamming window is used. To obtain vectorRead MoreSurvey On Sentiment Analysis And Opinion Mining2689 Words   |  11 Pages2002. Since SA is still in its nascent stage there are many open problems which constitute research areas in this field. E.g. many existing systems fail to detect sarcasm or irony. Word sense disambiguation is another challenging Natural Language Processing (NLP) problem which also exists in SA. Multimodal Sentiment Analysis is an emerging research area. Multimodal Sentiment Analysis refers to the combined use of two or more input modes to improve the performance of the analysis e.g. the combined