Elias Nemer

Robust voice activity detection using higher-order statistics in the LPC residual domain

This paper presents a robust algorithm for voice activity detection (VAD) based on newly established properties of the higher order statistics (HOS) of speech. Analytical expressions for the third and fourth-order cumulants of the LPC residual of short-term speech are derived assuming a sinusoidal model. The flat spectral feature of this residual results in distinct characteristics for these cumulants in terms of phase, periodicity and harmonic content and yields closed-form expressions for the skewness and kurtosis. Important properties about these cumulants and their similarity with the autocorrelation function are revealed from this exploratory part. They show that the HOS of speech are sufficiently distinct from those of Gaussian noise and can be used as a basis for speech detection. Their immunity to Gaussian noise makes them particularly useful in algorithms designed for low SNR environments. The proposed VAD algorithm combines HOS metrics with second-order measures, such as SNR and LPC prediction error, to classify speech and noise frames. The variance of the HOS estimators is quantified and used to yield a likelihood measure for noise frames. Moreover, a voicing condition for speech frames is derived based on the relation between the skewness and kurtosis of voiced speech. The performance of the algorithm is compared to the ITU-T G.729B VAD in various noise conditions, and quantified using the probability of correct and false classifications. The results show that the proposed algorithm has an overall better performance than G.729B, with noticeable improvement in Gaussian-like noises, such as street and parking garage, and moderate to low SNR.

Speech enhancement using fourth-order cumulants and optimum filters in the subband domain

A new method for speech enhancement using time-domain optimum filters and fourth-order cumulants (FOC) is proposed based on newly established properties of the FOC of speech signals. In the exploratory part of the paper, the analytical expression of the FOC of subbanded speech is derived assuming a sinusoidal model and up to two harmonics per band. Important properties about this cumulant are revealed and actual speech data is used to verify the derivations and the underlying model. In the application part of the work, speech enhancement is formulated as an estimation problem and the expression for the time-domain causal optimum filters is derived for a pth order system. The key idea is to use the FOC of the noisy speech to estimate the parameters required for the enhancement filters, namely the second-order statistics of the speech and noise. It is shown that the kurtosis and the diagonal slice of the FOC may be used to estimate such parameters as the SNR, the speech autocorrelation and the probability of speech presence in a given band. Subjective listening and examination of the spectrograms show that the resulting algorithm is effective on typical noises encountered in mobile telephony. Compared to the TIA-IS127 standard for noise reduction, it results in overall more noise reduction and better speech preservation in Gaussian, street and fan noise. Its effectiveness diminishes however in harmonic and impulsive types such as office and car engine, where discrimination between speech and noise based on FOC becomes more difficult.

Physical layer impairments in DVB-S2 receivers

Digital video broadcasting via satellite is being widely deployed worldwide. The first generation European standard (DVB-S) is a QPSK based system that supports up to 40 Msymb/s transmission rates. The second generation DVB-S2 specification recently finalized incorporates higher order modulations from 8PSK to 32 APSK. Physical layer impairments on the transmit-receive link include those introduced by the channel, such as reflections and interference, as well as those induced by various components in the system, such as tuner I/Q imbalance or amplifier non-linearity. These impairments degrade the received SNR and may in some cases affect the convergence behavior of various loops in the receiver. The paper provides a qualitative and quantitative description of the system and channel impairments and their effects on the received cluster SNR.