Music evokes profound emotions, yet the universality of emotional descriptors across languages remains debated. A key challenge in cross-cultural research on music emotion is biased stimulus selection and manual curation of taxonomies, predominantly relying on Western music and languages. To address this, we propose a balanced experimental design with nine online experiments in Brazil, the US, and South Korea, involving N=672 participants. First, we sample a balanced set of popular music from these countries. Using an open-ended tagging pipeline, we then gather emotion terms to create culture-specific taxonomies. Finally, using these bottom-up taxonomies, participants rate emotions of each song. This allows us to map emotional similarities within and across cultures. Results show consistency in high arousal, high valence emotions but greater variability in others. Notably, machine translations were often inadequate to capture music-specific meanings. These findings together highlight the need for a domain-sensitive, open-ended, bottom-up emotion elicitation approach to reduce cultural biases in emotion research.

More and more end-to-end text spotting methods based on Transformer architecture have demonstrated superior performance. These methods utilize a bipartite graph matching algorithm to perform one-to-one optimal matching between predicted objects and actual objects. However, the instability of bipartite graph matching can lead to inconsistent optimization targets, thereby affecting the training performance of the model. Existing literature applies denoising training to solve the problem of bipartite graph matching instability in object detection tasks. Unfortunately, this denoising training method cannot be directly applied to text spotting tasks, as these tasks need to perform irregular shape detection tasks and more complex text recognition tasks than classification. To address this issue, we propose a novel denoising training method (DNTextSpotter) for arbitrary-shaped text spotting. Specifically, we decompose the queries of the denoising part into noised positional queries and noised content queries. We use the four Bezier control points of the Bezier center curve to generate the noised positional queries. For the noised content queries, considering that the output of the text in a fixed positional order is not conducive to aligning position with content, we employ a masked character sliding method to initialize noised content queries, thereby assisting in the alignment of text content and position. To improve the model's perception of the background, we further utilize an additional loss function for background characters classification in the denoising training part.Although DNTextSpotter is conceptually simple, it outperforms the state-of-the-art methods on four benchmarks (Total-Text, SCUT-CTW1500, ICDAR15, and Inverse-Text), especially yielding an improvement of 11.3% against the best approach in Inverse-Text dataset.

Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. EC3 made his National Wrestling Alliance (NWA) debut at the company's 74th-anniversary show last year and a year later he defeated Tyrus for the Worlds Heavyweight Championship putting him on top of the historic promotion and ending the career of one of the most well-known performers in the business. Two months after capturing the title at the 75th-anniversary show, Thom Latimer used the "Lucky Seven Rule" to drop the NWA World Television Championship for a chance at EC3's title. The two will meet in a singles match at NWA Samhain later this month for the title. Better yet, EC3 gets to perform in front of his hometown fans in Cleveland, Ohio.

The game's historical politics are fascinating, and it does a great job of weaving in real history like Martin Luther's reform of the church, the Twelve Articles that were part of peasants' demands in 1525, as well as pagan and Roman myths. The game even highlights lesser known history, such as gay monks. Having seen the ending, and then nearly finishing a second playthrough, I appreciated how real history is at the core of the story's conflict. The class differences that are more easily swept under the rug during the first act of the game are still hinted at, as peasants note increased taxes and how rainfall collects downstream, making the farms more susceptible than the abbey to flooding. It's repeatedly mentioned that women can't own property, and depending on the playthrough, Andreas is able to help with that problem or not.

Natural Language Processing (NLP) is a discipline of AI which enables machines to understand and process human language. The project was about rewriting an existing song in a way that gives the song scientific or technological meaning. The project was based on simple NLP algorithms and not on big models like GPT-2, and still yield good results. The first step before the algorithmic tasks was to download a song's lyrics. In order to make things more interesting, I decided to download a random song each run.

When faced with hardships as an adult, throwing a tantrum may be irrational and inane. However, on the stage, tantrums are permitted -- and encouraged. I found myself collapsing through the hits, flying through the hardships, spinning through the confusion, jumping through happiness, pacing through anxiousness, and reaching out through desperation. It was there I stood naked and vulnerable. Allowing all of the frustration, doubts, and fears to unveil them on stage in front of an audience who wouldn't know the content, but could connect to the universal emotions. The art of dance is a powerful form of creative communication and expression, that oftentimes elicits this emotional, visceral response within an audience.