AN EFFICIENT SPEECH GENERATIVE MODEL BASED ON DETERMINISTIC/STOCHASTIC SEPARATION OF SPECTRAL ENVELOPES

The paper presents a speech generative model that provides an efficient way of generating speech waveform from its amplitude spectral envelopes. The model is based on hybrid speech representation that includes deterministic (harmonic) and stochastic (noise) components. The main idea behind the approach originates from the fact that speech signal has a determined spectral structure that is statistically bound with deterministic/stochastic energy distribution in the spectrum. The performance of the model is evaluated using an experimental low-bitrate wide-band speech coder. The quality of reconstructed speech is evaluated using objective and subjective methods. Two objective quality characteristics were calculated: Modified Bark Spectral Distortion (MBSD) and Perceptual Evaluation of Speech Quality (PESQ). Narrow-band and wide-band versions of the proposed solution were compared with MELP (Mixed Excitation Linear Prediction) speech coder and AMR (Adaptive Multi-Rate) speech coder, respectively. The speech base of two female and two male speakers were used for testing. The performed tests show that overall performance of the proposed approach is speaker-dependent and it is better for male voices. Supposedly, this difference indicates the influence of pitch highness on separation accuracy. In that way, using the proposed approach in experimental speech compression system provides decent MBSD values and comparable PESQ values with AMR speech coder at 6,6 kbit/s. Additional subjective listening testsdemonstrate that the implemented coding system retains phonetic content and speaker’s identity. It proves consistency of the proposed approach.

An Improved Frame Loss Concealment Algorithm Based on the Mixed Excitation Linear Prediction

An improved frame loss concealment algorithm based on the Mixed Excitation Linear Prediction (MELP) is presented in this paper. It introduces the Future frame to recover the lost frame and the intermediate frame (U/V frame and V/U frame) to determine the type of lost frame more accurately. Meanwhile, it proposes the Lagrange polynomial approach algorithm and the linear prediction algorithm to recover the parameters of lost frames in different frame types. The PESQ-MOS test shows that the synthetic speech quality has been improved with the algorithm which this paper has proposed.

Research on an Embedded Ultra-Low-Bit-Rate Speech Coding Algorithm

Ultra-low-bit-rate speech coding algorithm was in great demand for many fields such as underwater speech communications. Underwater speech communication for middle-long distance has the characteristics of narrow bandwidth as well as low transmission rate, which makes the underwater speech communication much difficult. Ultra-low-bit-rate speech coding algorithm plays an important role on this occasion. More over, it will be more flexible for the underwater speech communication system if the speech coding algorithm has an embedded structure. The paper introduced the principle of an embedded speech coding algorithm with dual rates at both 300bps and 400bps based on the enhanced mixed excitation linear prediction model. The results show that this embedded ultra-low-bit-rate speech coding algorithm has satisfactory quality under both DRT and MOS test.