Sentiment Analysis Across Multiple African Languages: A Current Benchmark

Sentiment analysis is a fundamental and valuable task in NLP. However, due to limitations in data and technological availability, research into sentiment analysis of African languages has been fragmented and lacking. With the recent release of the AfriSenti-SemEval Shared Task 12, hosted as a part of The 17th International Workshop on Semantic Evaluation, an annotated sentiment analysis of 14 African languages was made available. We benchmarked and compared current state-of-art transformer models across 12 languages and compared the performance of training one-model-per-language versus single-model-all-languages. We also evaluated the performance of standard multilingual models and their ability to learn and transfer cross-lingual representation from non-African to African languages. Our results show that despite work in low resource modeling, more data still produces better models on a per-language basis. Models explicitly developed for African languages outperform other models on all tasks. Additionally, no one-model-fits-all solution exists for a per-language evaluation of the models evaluated. Moreover, for some languages with a smaller sample size, a larger multilingual model may perform better than a dedicated per-language model for sentiment classification.Comment: Accepted to be published as part of SIAIA @ AAAI 202

Evaluating Novel Mask-RCNN Architectures for Ear Mask Segmentation

The human ear is generally universal, collectible, distinct, and permanent. Ear-based biometric recognition is a niche and recent approach that is being explored. For any ear-based biometric algorithm to perform well, ear detection and segmentation need to be accurately performed. While significant work has been done in existing literature for bounding boxes, a lack of approaches output a segmentation mask for ears. This paper trains and compares three newer models to the state-of-the-art MaskRCNN (ResNet 101 +FPN) model across four different datasets. The Average Precision (AP) scores reported show that the newer models outperform the state-of-the-art but no one model performs the best over multiple datasets.Comment: Accepted into ICCBS 202

Hey, Siri! Why Are You Biased against Women? (Student Abstract)

The intersection of pervasive technology and verbal communication has resulted in the creation of Automatic Speech Recognition Systems (ASRs), which automate the conversion of spontaneous speech into texts. ASR enables human-computer interactions through speech and is rapidly integrated into our daily lives. However, the research studies on current ASR technologies have reported unfulfilled social inclusivity and accentuated biases and stereotypes towards minorities. In this work, we provide a review of examples and evidence to demonstrate preexisting sexist behavior in ASR systems through a systematic review of research literature over the past five years. For each article, we also provide the ASR technology used, highlight specific instances of reported bias, discuss the impact of this bias on the female community, and suggest possible methods of mitigation. We believe this paper will provide insights into the harm that unchecked AI-powered technologies can have on a community by contributing to the growing body of research on this topic and underscoring the need for technological inclusivity for all demographics, especially women

Laboratory Study of the Cameron Bands and UV Doublet in the Middle Ultraviolet 180-300 nm by Electron Impact upon CO2 with Application to Mars

peer reviewedWe have observed electron impact fluorescence from CO2 to excite the Cameron bands (CBs), CO (a 3Π → X 1Σ+; 180-280 nm), the first-negative group (1NG) bands, CO+ (B 2Σ+ → X 2Σ+; 180-320 nm), the fourth-positive group (4PG) bands, CO (A 1Π → X 1Σ+; 111-280 nm), and the UV doublet, CO2+ ( B 2Σ u + → X 2Π g ; 288.3 and 289.6 nm) in the ultraviolet (UV). This wavelength range matches the spectral region of past and present spacecraft equipped to observe UV dayglow and aurora emissions from the thermospheres (100-300 km) of Mars and Venus. Our large vacuum system apparatus is able to measure the emission cross sections of the strongest optically forbidden UV transitions found in planetary spectra. Based on our cross-sectional measurements, previous CB emission cross-sectional errors exceed a factor of 3. The UV doublet lifetime is perturbed through B 2Σu + − A 2Π u spin-orbit coupling. Forward modeling codes of the Mars dayglow have not been accurate in the mid-UV due to systematic errors in these two emission cross sections. We furnish absolute emission cross sections for several band systems over electron energies 20-100 eV for CO2. We present a CB lifetime, which together with emission cross sections, furnish a set of fundamental physical constants for electron transport codes such as AURIC (Atmospheric Ultraviolet Radiance Integrated Code). AURIC and Trans-Mars are used in the analysis of UV spectra from the Martian dayglow and aurora

A single pseudouridine on rRNA regulates ribosome structure and function in the mammalian parasite Trypanosoma brucei

Abstract Trypanosomes are protozoan parasites that cycle between insect and mammalian hosts and are the causative agent of sleeping sickness. Here, we describe the changes of pseudouridine (Ψ) modification on rRNA in the two life stages of the parasite using four different genome-wide approaches. CRISPR-Cas9 knock-outs of all four snoRNAs guiding Ψ on helix 69 (H69) of the large rRNA subunit were lethal. A single knock-out of a snoRNA guiding Ψ530 on H69 altered the composition of the 80S monosome. These changes specifically affected the translation of only a subset of proteins. This study correlates a single site Ψ modification with changes in ribosomal protein stoichiometry, supported by a high-resolution cryo-EM structure. We propose that alteration in rRNA modifications could generate ribosomes preferentially translating state-beneficial proteins