We investigate four different privacy-sensitive features, namely energy, zero crossing rate, spectral flatness, and kurtosis, for speech detection in multiparty conversations. We liken this scenario to a meeting room and define our datasets and annotations accordingly. The temporal context of these features is modeled. With no temporal context, energy is the best performing single feature. But ...

This paper looks at the present standing of ecommerce in Saudi Arabia, as well as the challenges and strengths of Business to Customers (B2C) electronic commerce. Many studies have been conducted around the world in order to gain a better understanding of the demands, needs and effectiveness of online commerce. A study was undertaken to review the literature identifying the factors influencing ...

Vision based bin picking is increasingly more di cult as the complexity of target objects increases We propose an e cient solution where complex objects are su ciently represented by simple features cues thus invariance to object complexity is established The re gion extraction algorithm utilized in our approach is capable of providing the focus of attention to the simple cues as a trigger towa...

We present preliminary work on automatically scoring constructed responses elicited as part of a certification test designed to measure the effectiveness of the test-taker as a K-12 music teacher. This content scoring differs from most previous work in that the responses are relatively long and are written by an adult population of generally proficient English writers. We obtain reasonably good...

We show that people’s travel destinations are predictable based on simple features of their home and destination. Using geotagged Twitter data from over 200,000 people in the U.S., with a median of 10 visits per user, we use machine learning to classify whether or not a person will visit a given location. We find that travel distance is the most important predictive feature. Ignoring distance, ...