Emotional speech synthesis aims to synthesize human voices with various emotional effects. The current studies are mostly focused on imitating an averaged style belonging to a specific emotion type. In this paper, we seek to generate speech with a mixture of emotions at run-time. We propose a novel formulation that measures the relative difference between the speech samples of different emotions. We then incorporate our formulation into a sequence-to-sequence emotional text-to-speech framework. During the training, the framework does not only explicitly characterize emotion styles, but also explores the ordinal nature of emotions by quantifying the differences with other emotions. At run-time, we control the model to produce the desired emotion mixture by manually defining an emotion attribute vector. The objective and subjective evaluations have validated the effectiveness of the proposed framework. To our best knowledge, this research is the first study on modelling, synthesizing, and evaluating mixed emotions in speech.

Hive, the productivity platform provider, today announced the public release of HiveMind that uses Artificial Intelligence (AI) to automatically create a project plan in a matter of seconds. As Artificial Intelligence models are increasingly being integrated into content and note-taking platforms, Hive is pioneering the usage of the models' capacity for continuous learning and logical decision-making based on in-depth data. Modeled on six years of successful customer projects, HiveMind automatically sets out the steps to accomplish any goal, expediting project planning and execution. It has the ability to create project tasks based on simple suggestions, set next steps from received emails and reply based on the inbound email's content. "Today, superior performance in the marketplace comes from the depth of data you possess, and the ability to apply it quickly," said John Furneaux, Hive co-founder and CEO.

A South Carolina college philosophy professor is warning that we should expect a flood cheating with ChatGPT - a chatbot from OpenAI that's powered by artificial intelligence - after catching one of his students using it to generate an essay. Darren Hick, a philosophy professor at Furman University in Greenville, South Carolina, wrote a lengthy Facebook post this month detailing issues with the advanced chatbot and the'first plagiarist' he'd caught for a recent assignment to write 500 words on Hume and the paradox of horror. ChatGPT, which has been trained on a gigantic sample of text from the internet, can understand human language, conduct conversations with humans and generate detailed text that many have said is human-like and quite impressive. 'ChatGPT responds in seconds with a response that looks like it was written by a human--moreover, a human with a good sense of grammar and an understanding of how essays should be structured,' Hicks wrote. Darren Hick, a philosophy professor at Furman University in Greenville, South Carolina, wrote a lengthy Facebook post this month detailing issues with the advanced chatbot and the'first plagiarist' he'd caught for a recent assignment'The first indicator that I was dealing with A.I. is that, despite the syntactic coherence of the essay, it made no sense.'

Bengaluru, December 27, 2022: MIT xPRO has announced two new upskilling programs in Executive Leadership Principles and Machine Learning for Business, Engineering, and Science. Delivered through digital skills training platform Simplilearn, these programs leverage MIT xPRO's thought leadership in engineering and management developed over years of research, teaching, and practice as well as Simplilearn's dynamic, interactive, digital learning platform. The Executive Leadership Principles program is designed to enable learners to understand an array of organizational and leadership aspects. Some of the focus areas include organizational strategies and capabilities, applying influence, negotiation, conflict resolution, change management, problem solving, navigating culture and networks, as well as discovering and implementing leadership strengths. This Executive Program offers masterclasses taught by MIT faculty and instructors, assessments, case studies, and tools.

Many people use Twitter to catch up with the daily news. More importantly, Twitter is now seen as the go-to source of the latest information for professionals and experts in the field of science and technology. Here is the list of the top twenty influencers in artificial intelligence (AI) and machine learning (ML) (along with their AI Twitter accounts) that you can follow to keep up with the latest development in AI and ML. He is a top worldwide influencer since 2013, one of the TOP people to follow on Twitter. His interests include Data Science, Astrophysics, Machine Learning, Data Mining, and Space Science.

In the past few years, the number of people entering the field of data science has increased drastically because of higher salaries, an increasing job market, and more demand. Undoubtedly, there are unlimited programs to learn data science, several companies offering in-depth Data Science Bootcamp, and a ton of channels on YouTube that are covering data science content. The abundance of data science content can easily confuse one with where to begin or how to start their data science career. To ease this data science journey for beginners, intermediate, or starters, we are going to list a couple of data science tutorials, crash courses, webinars, and videos. The aim of this blog is to help beginners navigate their data science path, and also help them to determine if data science is the most perfect career choice for them or not.

Feature As word of students using AI to automatically complete essays continues to spread, some lecturers are beginning to rethink how they should teach their pupils to write. Writing is a difficult task to do well. The best novelists and poets write furiously, dedicating their lives to mastering their craft. The creative process of stringing together words to communicate thoughts is often viewed as something complex, mysterious, and unmistakably human. No wonder people are fascinated by machines that can write too.

The late Gabriel Opara was an African poet who wrote a lot of wonderful poems, including the popular "Piano and Drums," which is my favorite. I fell in love with the poem in my high school days when I did literature in English. Having completed the Deep Learning specialization and Tensorflow developer certification courses on Coursera, I decided to put my knowledge of Natural Language Processing into practice by applying AI to the things that interest me, of which African poems are one. Data collection is usually among the early stages of any machine learning project. I got all the data needed for this project from the public web. The data set consists of 14 poems by Gabriel in about 408 lines; the first 10 lines are the titles of the poems.

Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. During the application process for an AI-based company, I was given a take-home assessment that included a machine learning task.

In this paper, we present a deep learning-based framework for solving geometric construction problems through visual reasoning, which is useful for automated geometry theorem proving. Constructible problems in geometry often ask for the sequence of straightedge-and-compass constructions to construct a given goal given some initial setup. Our EuclidNet framework leverages the neural network architecture Mask R-CNN to extract the visual features from the initial setup and goal configuration with extra points of intersection, and then generate possible construction steps as intermediary data models that are used as feedback in the training process for further refinement of the construction step sequence. This process is repeated recursively until either a solution is found, in which case we backtrack the path for a step-by-step construction guide, or the problem is identified as unsolvable. Our EuclidNet framework is validated on complex Japanese Sangaku geometry problems, demonstrating its capacity to leverage backtracking for deep visual reasoning of challenging problems.