Recognizing Voice Over IP: A Robust Front-End for Speech Recognition on the World Wide Web

The Internet Protocol (IP) environment poses two relevant sources of distortion to the speech recognition problem: lossy speech coding and packet loss. In this paper, we propose a new front-end for speech recognition over IP networks. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bit stream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant benefits. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion due to the encoding-decoding process. Second, when packet loss occurs, our front-end becomes more effective since it is not constrained to the error handling mechanism of the codec. We have considered the ITU G.723.1 standard codec, which is one of the most preponderant coding algorithms in voice over IP (VoIP) and compared the proposed front-end with the conventional approach in two automatic speech recognition (ASR) tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated packet loss rates. Furthermore, the improvement is higher as network conditions worsen.Publicad

The Potential Importance of Non-Local, Deep Transport on the Energetics, Momentum, Chemistry, and Aerosol Distributions in the Atmospheres of Earth, Mars and Titan

A review of non-local, deep transport mechanisms in the atmosphere of Earth provides a good foundation for examining whether similar mechanisms are operating in the atmospheres of Mars and Titan. On Earth, deep convective clouds in the tropics constitute the upward branch of the Hadley Cell and provide a conduit through which energy, moisture, momentum, aerosols and chemical species are moved from the boundary layer to the upper troposphere and lower stratosphere. This transport produces mid-tropospheric minima in quantities such as water vapor and moist static energy and maxima where the clouds detrain. Analogs to this terrestrial transport are found in the strong and deep thermal circulations associated with topography on Mars and with Mars dust storms. Observations of elevated dust layers on Mars further support the notion that non-local deep transport is an important mechanism in the atmosphere of Mars. On Titan, the presence of deep convective clouds almost assures that non-local, deep transport is occurring and these clouds may play a role in global cycling of energy, momentum, and methane. Based on the potential importance of non-local deep transport in Earth's atmosphere and supported by evidence for such transport in the atmospheres of Mars and Titan, greater attention to this mechanism in extraterrestrial atmospheres is warranted.Comment: 25 pages, no figures, no table

Assessment of the Contribution of Traffic Emissions to the Mobile Vehicle Measured PM2.5 Concentration by Means of WRF-CMAQ Simulations

INE/AUTC 12.0

5G 3GPP-like Channel Models for Outdoor Urban Microcellular and Macrocellular Environments

For the development of new 5G systems to operate in bands up to 100 GHz, there is a need for accurate radio propagation models at these bands that currently are not addressed by existing channel models developed for bands below 6 GHz. This document presents a preliminary overview of 5G channel models for bands up to 100 GHz. These have been derived based on extensive measurement and ray tracing results across a multitude of frequencies from 6 GHz to 100 GHz, and this document describes an initial 3D channel model which includes: 1) typical deployment scenarios for urban microcells (UMi) and urban macrocells (UMa), and 2) a baseline model for incorporating path loss, shadow fading, line of sight probability, penetration and blockage models for the typical scenarios. Various processing methodologies such as clustering and antenna decoupling algorithms are also presented.Comment: To be published in 2016 IEEE 83rd Vehicular Technology Conference Spring (VTC 2016-Spring), Nanjing, China, May 201