Riddles based on simple puns can be dassified according to the patterns of word, syllable or phrase similarity they depend upon. We have devised a formal model ofthe semantic and syntactic regularities underlying some of the simpler types of punning riddle. We have also implemented thispreliminary theory in a Computer program which can generate riddles from a lexicon containing general data about words andphrases; that is, the lexicon content is not customized to produce jokes. An informal, formative evaluation of the program's results by a set of human judges suggests that the riddles produced by this program are of comparable quality to those in general circulation among school children.

Subvocal electromyogram (EMG) signal classification is used to control a modified web browser interface. Recorded surface signals from the larynx and sublingual areas below the jaw are filtered and transformed into features using a complex dual quad tree wavelet transform. Feature sets for six subvocally pronounced control words, 10 digits, 17 vowel phonemes and 23 consonant phonemes are trained using a scaled conjugate gradient neural network. The subvocal signals are classified and used to initiate web browser queries through a matrix based alphabet coding scheme. Hyperlinks on web pages returned by the browser are numbered sequentially and queried using digits only. Classification methodology, accuracy, and feasibility for scale up to real world human machine interface tasks are discussed in the context of vowel and consonant recognition accuracy.

We present results of electromyographic (EMG) speech recognition on a small vocabulary of 15 English words. EMG speech recognition holds promise for mitigating the effects of high acoustic noise on speech intelligibility in communication systems, including those used by first responders (a focus of this work). We collected 150 examples per word of single-channel EMG data from a male subject, speaking normally while wearing a firefighter's self-contained breathing apparatus. The signal processing consisted of an activity detector, a feature extractor, and a neural network classifier. Testing produced an overall average correct classification rate on the 15 words of 74% with a 95% confidence interval of (71%, 77%). Once trained, the subject used a classifier as part of a real-time system to communicate to a cellular phone and to control a robotic device. These tasks were performed under an ambient noise level of approximately 95 decibels. We also describe ongoing work on phoneme-level EMG speech recognition. Crown

We have developed a formal model of certain types of riddles, and implemented it in a computer program, JAPE, which generates simple punning riddles. In order to test the model, we evaluated the behaviour of the program, by having 120 children aged eight to eleven years old rate JAPE-generated texts, human-generated texts, and non-joke texts for "jokiness" and funniness. This confirmed that JAPE's output texts are indeed jokes, and that there is no significant difference in funniness or jokiness between JAPE"s most comprehensible texts and published human-generated jokes.

Autonomous, confidential training and treatment for behavioral health issues will need to be a critical component of long duration spaceflight travel. This work provides an evaluation of such a tool in a relevant ICE. Anderson AP, Fellows AM, Binsted KA, Hegel MT, Buckey JC. Autonomous, computer-based behavioral health countermeasure evaluation at HI-SEAS Mars analog. Aerosp Med Hum Perform. 2016; 87(11):912-920.

In an effort to focus on tractable problems, computational natural-language-understanding systems have typically addressed language phenomena that are amenable to combinatorial approaches using static and stereotypical semantic representations. Although such approaches are adequate for much of language, they're not easily extended to capture humans' more creative language interpretation capacities. An alternative tack is to begin by modeling less typical, more complex phenomena, with the goal of encompassing standard language as a trivial case. 1 Semantic interpretationSuppose you hear someone saying, "Everyone had so much fun diving from the tree into the swimming pool, we decided to put in a little … " At the point in the sentence where you hear the words "put in," you've already committed to an interpretation of the clause-probably that the owners are installing a diving board. Indeed, psycholinguistic research suggests that human sentence processing is both incremental and predictive, because people integrate perceptual input with linguistic and conceptual information at multiple levels of representation. 2 Neuroimaging research with magnetoencephalography suggests that after an initial modality-specific processing stage of approximately 200 milliseconds, speech processing is subserved by a bilateral network of inferior prefrontal and temporal lobe regions that are simultaneously active for hundreds of milliseconds. 3 Such data suggest that the processes of lexical access, semantic association, and contextual integration are simultaneous, as represented in cascade models.Besides its empirical motivation, incremental semantic processing has computational benefits for word recognition and contextual integration. Word recognition in natural speech, for example, is extremely challenging because of extensive variability in the acoustic input. Top-down semantic information greatly facilitates segmentation of the sound stream. Moreover, spoken language is produced quickly-typically at about two to three words per second-which necessitates parallel processing of linguistic cues and their semantic referents. Besides easing word recognition, activating the correct frame of reference greatly facilitates contextual integration. For instance, in the swimming pool example, knowledge of diving and the typical backyard pool lets you more easily recognize and inte- Computational Humor Kim Binsted, University of HawaiiNo, this is no April Fool's prank. Computer scientists at labs around the world are conducting serious research into … humor. Although it might seem whimsical, many excellent reasons exist to take a closer look at this fascinating aspect of human cognition and interaction.Humor affects attention and memory, facilitates social interaction, and ameliorates communication problems. If computers are ever going to communicate naturally and effectively with humans, they must be able to use humor. Moreover, humor provides insight into how humans process language-real, complex, creative language, not just a tractable s...

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