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This paper describes simulations of speech sequences transmission for intrusive measurement of voice transmission quality of service (VTQoS) in the environment of IP networks. The aim of the simulations was to investigate the impact of the different durations of speech sequences on speech quality from the jitter rate and packet loss point of view in IP networks. The ITU-T G.729 and ITU-T G.723.1 encoding schemes were used for the purpose of the simulations. The assessment of speech quality was realized by means of perceptual evaluation of speech quality (PESQ) algorithm. A comparison of the impact of different durations of speech sequences on speech quality and determination of the optimal duration of speech sequence for measurements of speech quality in telecommunication networks, is the aim of this paper.

Chunking is a key mechanism for sequence processing. Studies on speech sequences have suggested low-frequency cortical activity tracks spoken phrases, that is, chunks of words defined by tacit linguistic knowledge. Here, we investigate whether low-frequency cortical activity reflects a general mechanism for sequence chunking and can track chunks defined by temporarily learned artificial rules. The experiment records magnetoencephalographic (MEG) responses to a sequence of spoken words. To dissociate word properties from the chunk structures, two tasks separately require listeners to group pairs of semantically similar or semantically dissimilar words into chunks. In the MEG spectrum, a clear response is observed at the chunk rate. More importantly, the chunk-rate response is task-dependent. It is phase locked to chunk boundaries, instead of the semantic relatedness between words. The results strongly suggest that cortical activity can track chunks constructed based on task-related rules and potentially reflects a general mechanism for chunk-level representations.

Automatic phoneme segmentation of a speech sequence is a basic problem in speech engineering. This study investigates unsupervised phoneme segmentation without using prior information on linguistic contents and acoustic models of an input sequence. The authors formulate the unsupervised segmentation as an optimal problem by means of maximum likelihood, and show that the optimal segmentation corresponds to minimising the coding length of the input sequence. Under different assumptions, five different objective functions are developed, namely log determinant, rate distortion (RD), Bayesian log determinant, Mahalanobis distance and Euclidean distance objectives. The authors prove that the optimal segmentations have the transformation‐invariant properties, introduce a time‐constrained agglomerative clustering algorithm to find the optimal segmentations, and propose an efficient implementation of the algorithm by using integration functions. The experiments are carried out on the TIMIT database to compare the above five objective functions. The results show that RD achieves the best performance, and the proposed method outperforms the previous unsupervised segmentation methods. [ABSTRACT FROM AUTHOR]

This paper describes simulations of speech sequences transmission for intrusive measurement of voice transmission quality of service (VTQoS) in the environment of IP networks. The aim of the simulations was to investigate the impact of the different durations of speech sequences on speech quality from the jitter rate and packet loss point of view in IP networks. The ITU-T G.729 and ITU-T G.723.1 encoding schemes were used for the purpose of the simulations. The assessment of speech quality was realized by means of perceptual evaluation of speech quality (PESQ) algorithm. A comparison of the impact of different durations of speech sequences on speech quality and determination of the optimal duration of speech sequence for measurements of speech quality in telecommunication networks, is the aim of this paper. [ABSTRACT FROM AUTHOR]