Text-dependent Forensic Voice Comparison: Likelihood Ratio Estimation with the Hidden Markov Model (HMM) and Gaussian Mixture Model – Universal Background Model (GMMUBM) Approaches

Among the more typical forensic voice comparison (FVC) approaches, the acoustic-phonetic statistical approach is suitable for text-dependent FVC, but it does not fully exploit available time-varying information of speech in its modelling. The automatic approach, on the other hand, essentially deals with text-independent cases, which means temporal information is not explicitly incorporated in the modelling. Text-dependent likelihood ratio (LR)-based FVC studies, in particular those that adopt the automatic approach, are few. This preliminary LR-based FVC study compares two statistical models, the Hidden Markov Model (HMM) and the Gaussian Mixture Model (GMM), for the calculation of forensic LRs using the same speech data. FVC experiments were carried out using different lengths of Japanese short words under a forensically realistic, but challenging condition: only two speech tokens for model training and LR estimation. Log-likelihood-ratio cost (Cllr) was used as the assessment metric. The study demonstrates that the HMM system constantly outperforms the GMM system in terms of average Cllr values. However, words longer than three mora are needed if the advantage of the HMM is to become evident. With a seven-mora word, for example, the HMM outperformed the GMM by a Cllr value of 0.073

Enzyme engineering of fungal-derived FAD-GDH by circular permutation

The flavin adenine dinucleotide dependent glucose dehydrogenase (FAD-GDH; EC 1.1.5.9) comprises oxidoreductases that catalyze the initial oxidation of glucose and other sugar molecules, using FAD as the primary electron acceptor. FAD-GDH has received attention as biocatalyst for glucose monitoring, especially self-monitoring of blood glucose. Please click Additional Files below to see the full abstract

Protein engineering of Candida rugosa lipase

Lipases (EC 3.1.1.3) catalyze the hydrolysis of emulsified long-chain triacylglycerol at the lipid–water interface. Candida rugosa lipase (CRL) is one of important industrial enzymes that are widely used in biotechnological applications such as the production of fatty acids and the synthesis of various esters. The catalytic efficiency and substrate specificity are seemed to be the key factors for industrial applications. Several approaches have been used to increase the stability of different lipases. For example, the immobilized CRL on carriers led to significant improvement in the catalyst’s activity and stability (Ref 1). In this study, we have focused on protein engineering to improve the properties of CRL. Please click Additional Files below to see the full abstract