104744
Sentence-Internal Prosody Does not Help Parsing the Way Punctuation Does
This paper investigates the usefulness of sentence-internal prosodic cues in syntactic parsing of transcribed speech. Intuitively, prosodic cues would seem to provide much the same information in speech as punctuation does in text, so we tried to incorporate them into our parser in much the same way as punctuation is. We compared the accuracy of a statistical parser on the LDC Switchboard treebank corpus of transcribed sentence-segmented speech using various combinations of punctuation and sentence-internal prosodic information (duration, pausing, and f0 cues). With no prosodic or punctuation information the parser’s accuracy (as measured by F-score) is 86.9%, and adding punctuation increases its F-score to 88.2%. However, all of the ways we have tried of adding prosodic information decrease the parser’s F-score to between 84.8% to 86.8%, depending on exactly which prosodic information is added. This suggests that for sentence-internal prosodic information to improve speech transcript parsing, either different prosodic cues will have to used or they will have be exploited in the parser in a way different to that used currently.
2965282
Exploiting auxiliary distributions in stochastic unification-based grammars
This paper describes a method for estimating conditional probability distributions over the parses of "unification-based" grammars which can utilize auxiliary distributions that are estimated by other means. We show how this can be used to incorporate information about lexical selectional preferences gathered from other sources into Stochastic "Unification-based" Grammars (SUBGs). While we apply this estimator to a Stochastic Lexical-Functional Grammar, the method is general, and should be applicable to stochastic versions of HPSGs, categorial grammars and transformational grammars.
3264258
Type-driven semantic interpretation and feature dependencies in R-LFG
Once one has enriched LFG's formal machinery with the linear logic mechanisms needed for semantic interpretation as proposed by Dalrymple et. al., it is natural to ask whether these make any existing components of LFG redundant. As Dalrymple and her colleagues note, LFG's f-structure completeness and coherence constraints fall out as a by-product of the linear logic machinery they propose for semantic interpretation, thus making those f-structure mechanisms redundant. Given that linear logic machinery or something like it is independently needed for semantic interpretation, it seems reasonable to explore the extent to which it is capable of handling feature structure constraints as well. 
R-LFG represents the extreme position that all linguistically required feature structure dependencies can be captured by the resource-accounting machinery of a linear or similiar logic independently needed for semantic interpretation, making LFG's unification machinery redundant. The goal is to show that LFG linguistic analyses can be expressed as clearly and perspicuously using the smaller set of mechanisms of R-LFG as they can using the much larger set of unification-based mechanisms in LFG: if this is the case then we will have shown that positing these extra f-structure mechanisms is not linguistically warranted.
9027893
A Look at Parsing and Its Applications
This paper provides a brief introduction to recent work in statistical parsing and its applications. We highlight successes to date, remaining challenges, and promising future work.
2234445
Attention Shifting for Parsing Speech
We present a technique that improves the efficiency of word-lattice parsing as used in speech recognition language modeling. Our technique applies a probabilistic parser iteratively where on each iteration it focuses on a different subset of the word-lattice. The parser's attention is shifted towards word-lattice subsets for which there are few or no syntactic analyses posited. This attention-shifting technique provides a six-times increase in speed (measured as the number of parser analyses evaluated) while performing equivalently when used as the first-stage of a multi-stage parsing-based language model.
5925726
A Resource Sensitive Interpretation of Lexical Functional Grammar
This paper investigates whether the fundamental linguistic insights and intuitions of Lexical Functional Grammar (LFG), which is usually presented as a “constraint-based” linguistic theory, can be reformulated in a “resource sensitive” framework using a substructural modal logic. In the approach investigated here, LFG's f-descriptions are replaced with expressions from a multi-modal propositional logic (with permutation and possibly limited contraction). In effect, the feature structure “unification” basis of LFG's f-structures is replaced with a very different resource based mechanism. It turns out that some linguistic analyses that required non-monotonic devices in LFG (such as the “constraint equations” in the Andrews (1982) analysis of Icelandic) can be straightforwardly expressed in the framework presented here. Moreover, a Curry–Howard correspondence between proofs in this logic and λ-terms provides a semantic interpretation as a by-product of the process of showing syntactic well-formedness.
930298
On Compressing Encrypted Data without the Encryption Key
When it is desired to transmit redundant data over an insecure and bandwidth-constrained channel, it is customary to first compress the redundant data and then encrypt it for security reasons. In this paper, we investigate the novelty of reversing the order of these steps, i.e. first encrypting and then compressing. Although counter-intuitive, we show surprisingly that through the use of coding with side information principles, this reversal in order is indeed possible. In fact, for lossless compression, we show that the theoretical compression gain is unchanged by performing encryption before compression. We show that the cryptographic security of the reversed system is directly related to the strength of the key generator.
26304890
Speech signal enhancement through adaptive wavelet thresholding
This paper demonstrates the application of the Bionic Wavelet Transform (BWT), an adaptive wavelet transform derived from a non-linear auditory model of the cochlea, to the task of speech signal enhancement. Results, measured objectively by Signal-to-Noise ratio (SNR) and Segmental SNR (SSNR) and subjectively by Mean Opinion Score (MOS), are given for additive white Gaussian noise as well as four different types of realistic noise environments. Enhancement is accomplished through the use of thresholding on the adapted BWT coefficients, and the results are compared to a variety of speech enhancement techniques, including Ephraim Malah filtering, iterative Wiener filtering, and spectral subtraction, as well as to wavelet denoising based on a perceptually scaled wavelet packet transform decomposition. Overall results indicate that SNR and SSNR improvements for the proposed approach are comparable to those of the Ephraim Malah filter, with BWT enhancement giving the best results of all methods for the noisiest (-10db and -5db input SNR) conditions. Subjective measurements using MOS surveys across a variety of 0db SNR noise conditions indicate enhancement quality competitive with but still lower than results for Ephraim Malah filtering and iterative Wiener filtering, but higher than the perceptually scaled wavelet method.
7264850
Physically interactive story environments
Most interactive stories, such as hypertext narratives and interactive movies achieve an interactive "feel" by allowing the user to choose among multiple story paths. In this paper we discuss physically interactive environments with narrative structure in which the ability to choose among multiple story lines is replaced with having users, first, interact with the story characters in small, local "windows" of the narrative and, second, actively engage their bodies in movement, In particular, we found that compelling interactive narrative story systems can be perceived as highly responsive, engaging, and interactive even when the overall story has a single-path structure, in what we call a "less-choice, more-responsiveness" approach to the design of story-based interactive environments. We have also observed that unencumbering, rich sensor technology can facilitate user immersion in the experience as the story progresses--users can act as they typically would without worrying about manipulating a computer interface. To support these arguments, the paper describes the physical setup, the interactive story, the technology, and the user experience of four projects developed at the MIT Media Laboratory: KidsRoom, It/I, Personal Aerobics Trainer, and Swamped!
39453826
A software debugging glossary
This glossary contains 291 definitions of terms dealing with the debugging of computer software. The list includes numerous synonyms, as well as the proper names of debugging systems described in the open literature. Terms and definitions have been obtained from various sources: the software-engineering literature, other software-engineering glossaries, and individual contributions.
958169
Third-Order Moments of Filtered Speech Signals for Robust Speech Recognition
Novel speech features calculated from third-order statistics of subband-filtered speech signals are introduced and studied for robust speech recognition. These features have the potential to capture nonlinear information not represented by cepstral coefficients. Also, because the features presented in this paper are based on the third-order moments, they may be more immune to Gaussian noise than cepstrals, as Gaussian distributions have zero third-order moments. Experiments on the AURORA2 database studying these features in combination with Mel-frequency cepstral coefficients (MFCC's) are presented, and some improvement over the MFCC-only baseline is shown when clean speech is used for training, though the same improvement is not seen when multi-condition training data is used.