Author: SRI International

  • Class-dependent Score Combination for Speaker Recognition

    In this work, we are presenting a class-based score combination technique that relies on clustering of both the target models and the test utterances in a vector space defined by a set of speaker-specific transformation parameters estimated during transcription of the talker.

  • MLLR Transforms as Features in Speaker Recognition

    We explore the use of adaptation transforms employed in speech recognition systems as features for speaker recognition. This approach is attractive because, unlike standard frame-based cepstral speaker recognition models, it normalizes for the choice of spoken words in text-independent speaker verification.

  • Generation of fast interpreters for Huffman compressed bytecode

    Our approach uses canonical Huffman codes to generate compact opcodes with custom-sized operand fields and with a virtual machine that directly executes this compact code. In effect, this automatically creates both an instruction set for a customized virtual machine and an implementation of that machine.

  • Leveraging Speaker-dependent Variation of Adaptation

    This work introduces an automatic procedure for determining the size of regression class trees for individual speakers using an ensemble of speaker-level features to control the number of transformations, if any, that should be estimated by maximum likelihood linear regression.

  • Using MLP Features in SRI’s Conversational Speech Recognition System

    We describe the development of a speech recognition system for conversational telephone speech (CTS) that incorporates acoustic features estimated by multilayer perceptrons (MLP). The acoustic features are based on frame-level phone posterior probabilities, obtained by merging two different MLP estimators, one based on PLP-Tandem features, the other based on hidden activation TRAPs (HATs) features.

  • A Robust Method for Tracking Scene Text in Video Imagery

    We describe an approach that tracks planar regions of scene text that can undergo arbitrary 3-D rigid motion and scale changes. Our approach computes homographies on blocks of contiguous frames simultaneously using a combination of factorization and robust statistical methods.

  • Task Templates Based on Misconception Research (Padi Technical Report 6)

    This paper reports one such effort, motivated by assessments that elicit students’ qualitative explanations of situations that have been designed to provoke misconceptions and partial understandings. We describe four task-specific templates we created—three based on Hestenes, Wells, and Swackhamer’s Force Concept Inventory and one based on Novick and Nussbaums’s Test about Particles in a Gas.

  • Identifying and Segmenting Human-Motion for Mobile Robot Navigation using alignment errors

    This paper presents a new human-motion identification and segmentation algorithm from moving cameras. The algorithm is based on alignment error between pairs of moving object images. Pairs of object images generating relatively small alignment errors are used to estimate the fundamental frequency of the object motion.

  • Masquerade Detection via Customized Grammars

    We use the Sequitur algorithm to generate a context-free grammar which efficiently extracts repetitive sequences of commands executed by one user – which is mainly used to generate a profile of the user. This technique identifies also the common scripts implicitly or explicitly shared between users – a useful set of data for reducing false positives.

  • Evidence-Centered Assessment Design: Layers, Structures, and Terminology (Padi Technical Report 9)

    This presentation provides an overview of ECD, highlighting the ideas of layers in the process, structures and representations within layers, and terms and concepts that can be used to guide the design of assessments of practically all types. Examples are drawn from the Principled Assessment Designs for Inquiry (PADI) project.

  • Towards a Practical Stereo Vision Sensor

    This paper describes an experimental framework for determining these limits using image processing algorithms, operating on graphically synthesized imagery, with performance envelope validation on real stereo image data.

  • An Example-Based Exploration Of Design Patterns In Measurement (Padi Technical Report 8)

    This paper extends the work conducted by the Principled Assessment Designs for Inquiry (PADI) project to investigate more deeply the application of assessment design patterns.