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This paper studies the asymptotic properties (strong consistency, convergence rate, asymptotic normality) of a generalized weighted nonlinear least squares estimator under weak noise assumptions. Both deterministic and stochastic weighting are handled and the presence of model errors is considered.
Compounding is one of the most productive word formation processes in many languages and is therefore a main source of data sparsity in language modeling. Many solutions have been suggested to model compound words, most of which break the compound into its constituents and train a new model with them. In earlier work, we argued that this approach is suboptimal and we presented a novel technique that...
This paper proposes a novel approach for automatic estimation of four important traits of speakers, namely age, height, weight and smoking habit, from speech signals. In this method, each utterance is modeled using the i-vector framework which is based on the factor analysis on Gaussian Mixture Model (GMM) mean supervectors, and the Non-negative Factor Analysis (NFA) framework which is based on a...
In many criminal cases, evidence might be in the form of telephone conversations or tape recordings. Therefore, law enforcement agencies have been concerned about accurate methods to profile different characteristics of a speaker from recorded voice patterns, which facilitate the identification of a criminal. This paper proposes a new approach for speaker gender detection and age estimation, based...
We describe an algorithm to automatically estimate the voice onset time (VOT) of plosives. The VOT is the time delay between the burst onset and the start of periodicity when it is followed by a voiced sound. Since the VOT is affected by factors like place of articulation and voicing it can be used for inference of these factors. The algorithm uses the reassignment spectrum of the speech signal, a...
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