Publications
Efficient reconstruction of block-sparse signals
Summary
Summary
In many sparse reconstruction problems, M observations are used to estimate K components in an N dimensional basis, where N > M ¿ K. The exact basis vectors, however, are not known a priori and must be chosen from an M x N matrix. Such underdetermined problems can be solved...
Graph relational features for speaker recognition and mining
Summary
Summary
Recent advances in the field of speaker recognition have resulted in highly efficient speaker comparison algorithms. The advent of these algorithms allows for leveraging a background set, consisting a large numbers of unlabeled recordings, to improve recognition. In this work, a relational graph, where nodes represent utterances and links represent...
Matched filtering for subgraph detection in dynamic networks
Summary
Summary
Graphs are high-dimensional, non-Euclidean data, whose utility spans a wide variety of disciplines. While their non-Euclidean nature complicates the application of traditional signal processing paradigms, it is desirable to seek an analogous detection framework. In this paper we present a matched filtering method for graph sequences, extending to a dynamic...
An active filter achieving 43.6dBm OIP3
Summary
Summary
An active filter with a 50 omega buffer suitable as an anti-alias filter to drive a highly linear ADC is implemented in 0.13 um SiGe BiCMOS. This 6th-order Chebyshev filter has a 3 dB cutoff frequency of 28.3 MHz and achieves 36.5 dBm OIP3. Nonlinear digital equalization further improves OIP3...
A time-warping framework for speech turbulence-noise component estimation during aperiodic phonation
Summary
Summary
The accurate estimation of turbulence noise affects many areas of speech processing including separate modification of the noise component, analysis of degree of speech aspiration for treating pathological voice, the automatic labeling of speech voicing, as well as speaker characterization and recognition. Previous work in the literature has provided methods...
Assessing the speaker recognition performance of naive listeners using Mechanical Turk
Summary
Summary
In this paper we attempt to quantify the ability of naive listeners to perform speaker recognition in the context of the NIST evaluation task. We describe our protocol: a series of listening experiments using large numbers of naive listeners (432) on Amazon's Mechanical Turk that attempts to measure the ability...
Informative dialect recognition using context-dependent pronunciation modeling
Summary
Summary
We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align reference phones with dialect specific pronunciations to characterize when and how often substitutions, insertions, and deletions occur. Decision tree clustering is used to find...
NAP for high level language identification
Summary
Summary
Varying channel conditions present a difficult problem for many speech technologies such as language identification (LID). Channel compensation techniques have been shown to significantly improve performance in LID for acoustic systems. For high-level token systems, nuisance attribute projection (NAP) has been shown to perform well in the context of speaker...
The MIT LL 2010 speaker recognition evaluation system: scalable language-independent speaker recognition
Summary
Summary
Research in the speaker recognition community has continued to address methods of mitigating variational nuisances. Telephone and auxiliary-microphone recorded speech emphasize the need for a robust way of dealing with unwanted variation. The design of recent 2010 NIST-SRE Speaker Recognition Evaluation (SRE) reflects this research emphasis. In this paper, we...
Towards reduced false-alarms using cohorts
Summary
Summary
The focus of the 2010 NIST Speaker Recognition Evaluation (SRE) was the low false alarm regime of the detection error trade-off (DET) curve. This paper presents several approaches that specifically target this issue. It begins by highlighting the main problem with operating in the low-false alarm regime. Two sets of...