[PDF] Top 20 Speech recognition of mandarin syllables using both linear predict coding cepstra and Mel frequency cepstra
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Speech recognition of mandarin syllables using both linear predict coding cepstra and Mel frequency cepstra
... all mandarin syllables are monosyllables, the speech wave for each monosyllable is ...the recognition ability of the Bayes decision rule, which should not be damaged by the ambiguous ... See full document
12
Development Of Speech Recognition System For Forensic Application
... This speech analysis is important step and also the first step in the automatic speech recognition ...input speech signal with the acoustic parameters and for subsequent used by the acoustic ... See full document
24
Volume 1, Issue 3, November 2012 Page 69
... for speech processing corresponding to 16 kHz to 22 ...various speech features extraction techniques, including Linear Predictive Coding (LPC), Perceptual Linear Prediction (PLP) and ... See full document
6
Title: Speech Feature Extraction Techniques: A Review
... identify speech from multiple users, the user needs to be in a place which is background noise free for an accurate recognition, there occurs a problem with the accent and the pronunciation of the user or ... See full document
8
Review on Computer Control with Voice Command (MFCC) using Ad-hoc Network
... in recognition of speech under stress and formulates new features which are shown to improve stressed speech ...effect speech, and noisy actual stressed speech from the SUSAS database ... See full document
6
Accent Recognition using MFCC and LPC with Acoustic Features
... in speech increases recognition rate, but success rates vary among ...of speech signal. Mel Frequency Cepstral Coefficient (MFCC) and Linear Productive Coding (LPC) are ... See full document
7
Robust Speech Recognition System Using Conventional and Hybrid Features of MFCC, LPCC, PLP, RASTA PLP and Hidden Markov Model Classifier in Noisy Conditions
... of speech recognition (SR) has been one of the most active areas of ...hybrid speech feature ex- traction algorithms of Mel Frequency Cepstrum Coefficient (MFCC), Linear ... See full document
9
Emotion recognition using Speech Signal: A Review
... (Mel Frequency Cepstrum Coefficient) provide the highest accuracy on all databases provided using the linear kernel [6] and the spectral coefficients derived from LPC (Linear Predictive ... See full document
7
A Review on Neural Network based Noise Robust Speech Recognition Methods
... beings. Speech is a natural way of communication because it requires no special training as most of the humans are born with this ...if speech is used for Human Machine Interface ...ASR, Speech is ... See full document
7
Analysis of Feature Extraction Methods for Speech Recognition
... by speech recognition. In speech recognition, feature extraction is the most imperative ...input speech that help the system in identifying the ...like linear predictive ... See full document
6
Quality Estimation of Speech Recognition Features for Dynamic Time Warping Classifier
... the speech recordings of four speakers, including two males and two ...of speech corpus was 11025 Hz, 16-bits/sample, ...isolated speech items recognition ...order Linear ... See full document
6
Speech Recognition in ATMs: Application of Linear Predictive Coding and Support Vector Machines
... a speech recognition system is developed for financial transactions in ATMs using Linear Predictive Coding (LPC) and Support Vector Machines ...processed using LPC for extracting ... See full document
6
Speaker recognition with hybrid features from a deep belief network
... that using hybrid features is promising and improves performance on speaker classification ...speaker recognition is a language independent task, the proposed framework can be extended for speech ... See full document
12
Speaker Recognition System and Algorithms
... human speech could be a signal containing mixed styles of information; as well as words, feelings, language and identity of the ...correct recognition of persons is ...person) recognition is that the ... See full document
5
Fuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition
... These traditional clustering approaches generate partitions and every pattern is associated with one and only one cluster. Hence, the clusters are disjoint in such a hard clustering approach. Fuzzy clustering extends ... See full document
8
A parametric prosody coding approach for Mandarin speech using a hierarchical prosodic model
... 24-dimensional mel-generalized cepstral coef- ficients (MGC) [50], delta MGCs, delta-delta MGCs, energy, delta energy, and delta-delta ...by using the context ... See full document
24
THE LEARNING METHOD OF SPEECH RECOGNITION BASED ON HMM
... The arrows leaving a state are annotated with a probability that indicates how likely it is that this particular transition out of the state will be chosen. As a transition has to be made the probabilities associated ... See full document
7
Cross Breed Biometric Fusion at Feature Level Using Back Propagation Algorithm
... Physical access and internal access are used to venture computers and systems. A biometric scanning machine takes a biometric data like a speech or tongue-print scan and converts it into digital in sequence a ... See full document
5
Optimization the Parameters for Speech Recognition System Using Genetic Algorithm
... improve speech recognition ...However, speech recognition rate still has room for improvement, where much effort is needed to improve GA method for accelerating the learning process in HMM ... See full document
8
Experimental Results for Baseline Speech Recognition Performance using Input Acquired from a Linear Microphone Array
... Experimental Results for Baseline Speech Recognition Performance using Input Acquired from a Linear Microphone Array Experimental Results for Baseline Speech Recognition Performance using Input Acquir[.] ... See full document
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