A Speech Quality Classifier based on Tree-CNN Algorithm that Considers Network Degradations

Many factors can affect the users’ quality of experience (QoE) in speech communication services. The impairment factors appear due to physical phenomena that occur in the transmission channel of wireless and wired networks. The monitoring of users’ QoE is important for service providers. In this context, a non-intrusive speech quality classifier based on the Tree Convolutional Neural Network (Tree-CNN) is proposed. The Tree-CNN is an adaptive network structure composed of hierarchical CNNs models, and its main advantage is to decrease the training time that is very relevant on speech quality assessment methods. In the training phase of the proposed classifier model, impaired speech signals caused by wired and wireless network degradation are used as input. Also, in the network scenario, different modulation schemes and channel degradation intensities, such as packet loss rate, signal-to-noise ratio, and maximum Doppler shift frequencies are implemented. Experimental results demonstrated that the proposed model achieves significant reduction of training time, reaching 25% of reduction in relation to another implementation based on DRBM. The accuracy reached by the Tree-CNN model is almost 95% for each quality class. Performance assessment results show that the proposed classifier based on the Tree-CNN overcomes both the current standardized algorithm described in ITU-T Rec. P.563 and the speech quality assessment method called ViSQOL

Reviews on Technology and Standard of Spatial Audio Coding

Market  demands  on a more impressive entertainment media have motivated for delivery of three dimensional  (3D) audio content to  home consumers  through Ultra  High  Definition  TV  (UHDTV), the next generation of TV broadcasting, where spatial  audio  coding plays  fundamental role. This paper reviews fundamental concept on spatial audio coding which includes technology, standard, and application. Basic principle of object-based audio reproduction system  will also be elaborated, compared  to  the  traditional channel-based system, to provide good understanding on this popular interactive audio reproduction system which gives end users flexibility to render  their  own preferred  audio composition.Keywords : spatial audio, audio coding, multi-channel audio signals, MPEG standard, object-based audi

Scalable and perceptual audio compression

This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner

Using a low-bit rate speech enhancement variable post-filter as a speech recognition system pre-filter to improve robustness to GSM speech

Includes bibliographical references.Performance of speech recognition systems degrades when they are used to recognize speech that has been transmitted through GS1 (Global System for Mobile Communications) voice communication channels (GSM speech). This degradation is mainly due to GSM speech coding and GSM channel noise on speech signals transmitted through the network. This poor recognition of GSM channel speech limits the use of speech recognition applications over GSM networks. If speech recognition technology is to be used unlimitedly over GSM networks recognition accuracy of GSM channel speech has to be improved. Different channel normalization techniques have been developed in an attempt to improve recognition accuracy of voice channel modified speech in general (not specifically for GSM channel speech). These techniques can be classified into three broad categories, namely, model modification, signal pre-processing and feature processing techniques. In this work, as a contribution toward improving the robustness of speech recognition systems to GSM speech, the use of a low-bit speech enhancement post-filter as a speech recognition system pre-filter is proposed. This filter is to be used in recognition systems in combination with channel normalization techniques

Real-Time Implementation Of LPC-10 Codec On TMS320C6713 DSP

During last two decades various speech coding algorithms have been developed. The range of toll speech frequency is from 300 Hz- 3400 Hz. Generally, human speech signal could be classified as non-stationary signal because of its fluctuation randomly over the time axis. One important assumption made to make the analysis of such signal even easier by assuming the speech signal is quasi-stationary over short range (frame). The frames of speech signal can be classified further into Voiced or Unvoiced, where the voiced part is quasi-stationary while the unvoiced part as an AWGN. The quality of the synthesized signal is degraded significantly due to the excitation of voiced part not equally spaced within the frame and the excitation of the unvoiced part is not exact AWGN. This assumption produced a non-natural speech signal but with high intelligible level. One more reason is that the frame could have voiced plus unvoiced parts within the same frame, and by classifying this frame as voiced or unvoiced due to rigid decision would drop the level of quality significantly. Speech compression commonly referred to as speech coding, where the amount of redundancies is reduced, and represent the speech signal by set of parameters in order to have very low bit rates. One of these speech coding algorithms is linear predictive coding (LPC-10). This thesis implements LPC-10 analysis and synthesis using Matlab and C coding. LPC-10 have been compared with some other speech compression algorithms like pulse code modulation (PCM), differential pulse code modulation (DPCM), and code excited linear prediction coding (CELP), in term of segmental signal to quantization noise ratio SEG-SQNR and mean squared error MSE using Matlab simulation. The focus on LPC-10 was implemented on the DSP board TMS320C6713 to test the LPC-10 algorithm in realtime. Real-time implementation on TMS320C6713 DSP board required to convert the Matlab script into C code on the DSP Board. Upon successfully completion, comparison of the results using TMS320C6713 DSP against the simulated results using Matlab in both graphical and tabular forms were made

Analysis by synthesis spatial audio coding

This study presents a novel spatial audio coding (SAC) technique, called analysis by synthesis SAC (AbS-SAC), with a capability of minimising signal distortion introduced during the encoding processes. The reverse one-to-two (R-OTT), a module applied in the MPEG Surround to down-mix two channels as a single channel, is first configured as a closed-loop system. This closed-loop module offers a capability to reduce the quantisation errors of the spatial parameters, leading to an improved quality of the synthesised audio signals. Moreover, a sub-optimal AbS optimisation, based on the closed-loop R-OTT module, is proposed. This algorithm addresses a problem of practicality in implementing an optimal AbS optimisation while it is still capable of improving further the quality of the reconstructed audio signals. In terms of algorithm complexity, the proposed sub-optimal algorithm provides scalability. The results of objective and subjective tests are presented. It is shown that significant improvement of the objective performance, when compared to the conventional open-loop approach, is achieved. On the other hand, subjective test show that the proposed technique achieves higher subjective difference grade scores than the tested advanced audio coding multichannel