Experimental Study on Performance Analysis of Viterbi Algorithm based on Hidden Markov Model considering Soft Decision Decoding
نویسندگان
چکیده
Convolutional code is relatively popular technique in decreasing the bit error rate (BER). The transmitted data under Additive white Gaussian noise (AWGN) channel can be successfully recovered at the receiver side by using Viterbi algorithm based on hidden Markov model (HMM) to decode and correct the data. Viterbi algorithm work by calculating the hamming distance, comparing the path metric, and then decide the receiver bit stream to the trellis diagram. In this paper, several parameters and techniques in Viterbi algorithm are investigated to achieve best performance in decoding the received data.
منابع مشابه
Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM
Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...
متن کاملGeneralized Baum-Welch and Viterbi Algorithms Based on the Direct Dependency among Observations
The parameters of a Hidden Markov Model (HMM) are transition and emission probabilities‎. ‎Both can be estimated using the Baum-Welch algorithm‎. ‎The process of discovering the sequence of hidden states‎, ‎given the sequence of observations‎, ‎is performed by the Viterbi algorithm‎. ‎In both Baum-Welch and Viterbi algorithms‎, ‎it is assumed that...
متن کاملRobust speech recognition based on a Bayesian prediction approach
In this paper, we study a category of robust speech recognition problem in which mismatches exist between training and testing conditions, and no accurate knowledge of the mismatch mechanism is available. The only available information is the test data along with a set of pretrained Gaussian mixture continuous density hidden Markov models (CDHMM’s). We investigate the problem from the viewpoint...
متن کاملScore Following Using Spectral Analysis and Hidden Markov Models
This paper presents an approach to score following. The realtime alignment of a performance with a score is obtained through the use of a hidden Markov model. The model works on two levels. The lower level compares the features of the incoming signal with the expected ones. Groups of states of the lower level are embedded in states at the higher level, which are used to model the performance by...
متن کاملKL-Divergence Guided Two-Beam Viterbi Algorithm on Factorial HMMs
This thesis addresses the problem of the high computation complexity issue that arises when decoding hidden Markov models (HMMs) with a large number of states. A novel approach, the two-beam Viterbi, with an extra forward beam, for decoding HMMs is implemented on a system that uses factorial HMM to simultaneously recognize a pair of isolated digits on one audio channel. The two-beam Viterbi alg...
متن کامل