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Speaker recognition systems trained on long duration utterances are known to perform significantly worse when short test segments are encountered. To address this mismatch, we analyze the effect of duration variability on phoneme distributions of speech utterances and i-vector length. We demonstrate that, as utterance duration is decreased, number of detected unique phonemes and i-vector length approaches zero in a logarithmic and non-linear fashion, respectively. Assuming duration variability as an additive noise in the ivector space, we propose three different strategies for its compensation: i) multi-duration training in Probabilistic Linear Discriminant Analysis (PLDA) model, ii) score calibration using log duration as a Quality Measure Function (QMF), and iii) multi-duration PLDA training with synthesized short duration i-vectors. Experiments are designed based on the 2012 National Institute of Standards and Technology (NIST) Speaker Recognition Evaluation (SRE) protocol with varying test utterance duration. Experimental results demonstrate the effectiveness of the proposed schemes on short duration test conditions, especially with the QMF calibration approach.

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Purpose – The purpose of this paper is to analyze the relationship between financial disclosure and the financial performance of microfinance institutions (MFIs). Design/methodology/approach – The paper utilizes ordinary least squares method to analyze the impact of disclosure on financial performance, an ordered probit model to investigate the possible effect of financial performance on disclosure and utilizes a three-stage least squares method to delineate the endogenous relationship between disclosure and financial performance of MFIs. Findings – The paper finds that better disclosure has a statistically significant positive impact on operational performance of MFIs; second, it also shows that improved financial performance results in better financial disclosure. Keeping the endogenous nature of the relationship between disclosure and performance, the paper uses a three-stage least squares method to show that disclosure and financial performance positively affect each other simultaneously. Research limitations/implications – The paper attempts to delineate a positive association between better disclosure on financial performance of MFIs, which can be used for developing a better disclosure policy by management, formulating more effective guidelines for disclosure by the stakeholders and mandating more appropriate laws and uniform disclosure practice by regulators. Originality/value – This is the first study that uses a large number of MFIs from 75 countries; second, it uses a uniform scale of designating a disclosure rating (assigned by MIX Market) to show the relationship between disclosure and performance. Finally, it uses three-stage least squares method to address the possible endogeneity between disclosure and performance.

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