Bell Labs

About: Bell Labs is a based out in . It is known for research contribution in the topics: Laser & Optical fiber. The organization has 36499 authors who have published 59862 publications receiving 3190823 citations. The organization is also known as: Bell Laboratories & AT&T Bell Laboratories.

Steiner tree problems

Abstract: We give a survey up to 1989 on the Steiner tree problems which include the four important cases of euclidean, rectilinear, graphic, phylogenetic and some of their generalizations. We also provide a rather comprehensive and up-to-date bibliography which covers more than three hundred items.

A stochastic model of human-machine interaction for learning dialog strategies

Abstract: We propose a quantitative model for dialog systems that can be used for learning the dialog strategy. We claim that the problem of dialog design can be formalized as an optimization problem with an objective function reflecting different dialog dimensions relevant for a given application. We also show that any dialog system can be formally described as a sequential decision process in terms of its state space, action set, and strategy. With additional assumptions about the state transition probabilities and cost assignment, a dialog system can be mapped to a stochastic model known as Markov decision process (MDP). A variety of data driven algorithms for finding the optimal strategy (i.e., the one that optimizes the criterion) is available within the MDP framework, based on reinforcement learning. For an effective use of the available training data we propose a combination of supervised and reinforcement learning: the supervised learning is used to estimate a model of the user, i.e., the MDP parameters that quantify the user's behavior. Then a reinforcement learning algorithm is used to estimate the optimal strategy while the system interacts with the simulated user. This approach is tested for learning the strategy in an air travel information system (ATIS) task. The experimental results we present in this paper show that it is indeed possible to find a simple criterion, a state space representation, and a simulated user parameterization in order to automatically learn a relatively complex dialog behavior, similar to one that was heuristically designed by several research groups.

On the use of autocorrelation analysis for pitch detection

Abstract: One of the most time honored methods of detecting pitch is to use some type of autocorrelation analysis on speech which has been appropriately preprocessed. The goal of the speech preprocessing in most systems is to whiten, or spectrally flatten, the signal so as to eliminate the effects of the vocal tract spectrum on the detailed shape of the resulting autocorrelation function. The purpose of this paper is to present some results on several types of (nonlinear) preprocessing which can be used to effectively spectrally flatten the speech signal The types of nonlinearities which are considered are classified by a non-linear input-output quantizer characteristic. By appropriate adjustment of the quantizer threshold levels, both the ordinary (linear) autocorrelation analysis, and the center clipping-peak clipping autocorrelation of Dubnowski et al. [1] can be obtained. Results are presented to demonstrate the degree of spectrum flattening obtained using these methods. Each of the proposed methods was tested on several of the utterances used in a recent pitch detector comparison study by Rabiner et al. [2] Results of this comparison are included in this paper. One final topic which is discussed in this paper is an algorithm for adaptively choosing a frame size for an autocorrelation pitch analysis.

New Phases of C60 Synthesized at High Pressure

Abstract: The fullerene C60 can be converted into two different structures by high pressure and temperature. They are metastable and revert to pristine C60 on reheating to 300°C at ambient pressure. For synthesis temperatures between 300° and 400°C and pressures of 5 gigapascals, a nominal face-centered-cubic structure is produced with a lattice parameter ao = 13.6 angstroms. When treated at 500° to 800°C at the same pressure, C60 transforms into a rhombohedral structure with hexagonal lattice parameters of ao = 9.22 angstroms and co = 24.6 angstroms. The intermolecular distance is small enough that a chemical bond can form, in accord with the reduced solubility of the pressure-induced phases. Infrared, Raman, and nuclear magnetic resonance studies show a drastic reduction of icosahedral symmetry, as might occur if the C60 molecules are linked.

Multiresolution signal processing for meshes

Abstract: We generalize basic signal processing tools such as downsampling, upsampling, and filters to irregular connectivity triangle meshes. This is accomplished through the design of a non-uniform relaxation procedure whose weights depend on the geometry and we show its superiority over existing schemes whose weights depend only on connectivity. This is combined with known mesh simplification methods to build subdivision and pyramid algorithms. We demonstrate the power of these algorithms through a number of application examples including smoothing, enhancement, editing, and texture mapping.