Robust FM demodulation of discrete-time signals using least squares differential ratio

A technique for the robust demodulation of discrete FM signals in the presence of additive noise is presented. Based upon least squares, the proposed technique is shown to improve the accuracy of instantaneous frequency estimation by 17 to 79% compared with the popular discrete energy separation (DESA), smooth DESA and Hilbert transform-based algorithms, e.g. noisy signals at low SNRs.     

Estimating the pitch period of voiced speech

In speech processing an estimation of the speech pitch period is important. Real time pitch detection is only possible by the selection of an efficient algorithm suitable for implementation on a programmable processor or in special-purpose hardware. The use of the periodogram algorithm (p.a.) is proposed to detect the pitch period of voiced speech. This algorithm is attractive for the following reasons: (a) it has no multiply operation; (b) when implemented on a 16-bit computer (e.g. microprocessor) the computation can be done in integer arithmetic without exceeding the microprocessor's dynamic range; (c) it is a simple technique for estimating the pitch period with reasonable accuracy. Results of the analysis of speech signals and sinusoids using the periodogram algorithm are presented and comparisons are made with the average magnitude difference function (a.m.d.f.) which is an alternative method of estimating the pitch period of the voiced speech.     

Tablet PC and Electronic Whiteboard Use in Signal Processing Education [DSP Education]

This paper discusses the innovative use of the Tablet PC for lectures and the electronic whiteboard for tutorial discussions and laboratories. The paper also presents the new evaluation results on the use of the electronic whiteboard for prerecorded lectures that combine a synchronized lecturer video with dynamic annotation. The results clearly show that signal processing students feel they can review and understand lecture material more effectively with this method. Moreover, their examination performances suggest that higher levels of understanding may be achieved     

The time-domain periodogram algorithm

The Time-Domain Periodogram Algorithm (TDPA) is proposed for estimating the pitch period of voiced speech sounds. After the algorithm has been presented theoretically, experimental results of the analysis of speech signals and sinusoids using the TDPA are given and the algorithm's noise performance is also evaluated. These results compare favourably with the average magnitude difference function (AMDF). The TDPA is highly suitable for implementation on a 16-bit microprocessor, since it uses no multiply operations and the computation can be performed in integer arithmetic without exceeding the dynamic range of the microprocessor. The TDPA also provides as a byproduct a well behaved estimate of signal intensity.     

Language-Dependent Contribution Measuring and Weighting for Combining Likelihood Scores in Language Identification Systems

Developing a fusion-based system is one of the key research issues in modern Language Identification (LID) systems. In this paper we investigate existing fusion techniques for LID systems and propose an alternative solution. By directly utilizing language-dependent contribution information, a novel Language-Dependent Weighting approach is introduced and implemented. We investigate various contribution measures, including LID performances, likelihood ratios, and Kullback–Leibler divergence. These measures are conducted from either development datasets or class models. The advantage of using language-dependent weighting over language-independent weighting is illustrated using a Language-Dependent Contribution Map. Both the OGI and CallFriend databases show a very similar contribution pattern which is related to language characteristics. Experiments on the NIST LRE 2003 task and OGI database demonstrate that the proposed fusion technique outperforms other recent fusion techniques when the amount of available development data is limited. In particular, the system based on Kullback-Leibler divergence achieved the best performance while eliminating the need for development data.     

Technique for performing multiplication on a 16-bit microprocessor using an extension of Booth's algorithm

Multiplication of a 2's-complement number by a known coefficient is often required in digital signal processing and other applications. When this is required to be performed on a microprocessor, an extension of Booth's algorithm (e.b.a.) can be used. Examples are presented to demonstrate how the multiplication is performed using e.b.a. on a microprocessor, and comparisons are made with the machine multiply instruction (m.m.i.) which show that the e.b.a. can take significantly less machine time.