Subjective comparison and evaluation of speech enhancement algorithms
Speech Communication
Single-Ended Speech Quality Measurement Using Machine Learning Methods
IEEE Transactions on Audio, Speech, and Language Processing
Evaluation of Objective Quality Measures for Speech Enhancement
IEEE Transactions on Audio, Speech, and Language Processing
| Hi-index | 0.00 |
Today, the primary constrain in wireless communication system is limited bandwidth and power. Wireless systems involved in transmission of speech envisage that efficient and effective methods need to be developed for maintaining quality-of-speech, especially at the receiving end, with maximum saving of bandwidth and power. Amongst all elements of the communication system (transmitter, channel and receiver), transmission channel (carrier of information/data, also called the medium) is the most critical and plays a key role in the transmission and reception of information/data. Channel conditions decide the quality of speech at receiver. Modeling a channel is a complex task. Many techniques are adopted to mitigate the effect of the channel. AMR (Adaptive Multi Rate) is one such technique that counteracts the deleterious effect of the channel on speech. This technique employs variable bit rate that dynamically switches to specific modes of operation (switching bit rates--called modes of operation) depending upon the channel conditions.In this paper, the application of Code Excited Linear Prediction (CELP) source coder on speech followed by AMR codec is investigated and studied. An e-test bench using MATLAB is created to implement the CELP based AMR Codec scheme, and the same studied and investigated through a series of simulation. Here, both subjective and objective evaluations are carried out. Objective evaluations are categorized into waveform based, spectral based and perceptual based analysis. The results of the simulations are recorded and compared in various graphs and tables, which include calculation of various parameters like Absolute Error (ABS), Mean Square Error (MSE), Root Mean Square Error (RMSE), Signal to Noise Ratio (SNR), segmental SNR (segSNR) (Y. Hu and P. Loizou in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., vol. 1, pp. 153---156, 2006a; Proc. Interspeech, pp. 1447---1450, 2006b), Weighted-Slope Spectral distance (WSS) (Y. Hu and P. Loizou in Speech Commun. 49, 588---601, 2007), Perceptual Evaluation of Speech Quality (PESQ) (ITU-T rec. P.862, 2000), Log-Likelihood Ratio (LLR), Itakura-Saito Distance measure (ISD), Cepstrum Distance Measures (CEP) (V. Turbin and N. Faucheur in Proc. Online Workshop Meas. Speech Audio Quality Netw., pp. 81---84, 2005), Frequency Weighted Segmental SNR (fwSNRseg), Predicted rating of overall Quality (Covl), Rating of Speech Distortion (Csig), Rating of Background Distortion (Cbak) (ITU-T rec. P.835, 2003) and MeanOpinion Score (MOS). Simulation results clearly advocate that, it is possible to producevariable bitrates (tuning to channel conditions) in CELP coder by affecting coefficients of the coder while still maintaining a good quality of speech. Further, higher the bit-rate used, the better is the quality of speech (which can be verified from the results obtained with PESQ and MOS analysis) and at the same time offered simulation delay time also increases.