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With output up to 123 dB, smooth coverage and sonic clarity down to 37 Hz, the EON ONE MKII is a portable and comprehensive column-style speaker system that can support a wide range of activities for BCIS students and faculty, from performances and presentations to seminars and sporting events. Engineered with ease-of-use as the top priority, the EON ONE MKII also features a Triple-Tier DSP that allows users to choose between beginner, intermediate or advanced controls for quickly finding the ideal sound for users of any experience level. Along with the on-board controls, students and faculty can also wirelessly control the systems from their smart device thanks to the JBL Pro Connect app.
A spokesperson for BCIS noted how equipping students with the best systems to fuel their passion for music and the arts is a top priority for faculty and staff, and that the EON ONE MK2 is a finely designed product that checks all of the boxes. They thanked PGI and HARMAN for providing the school excellent and seamless audio solution to support a wide range of school activities.
Azure AI Speech service offers advanced speech to text capabilities. This feature supports both real-time and batch transcription, providing versatile solutions for converting audio streams into text.
Real-time speech to text can be accessed via the Speech SDK, Speech CLI, and REST API, allowing integration into various applications and workflows.Real-time speech to text is available via the Speech SDK, the Speech CLI, and REST APIs such as the Fast transcription API.
Fast transcription API is used to transcribe audio files with returning results synchronously and faster than real-time audio. Use fast transcription in the scenarios that you need the transcript of an audio recording as quickly as possible with predictable latency, such as:
With custom speech, you can evaluate and improve the accuracy of speech recognition for your applications and products. A custom speech model can be used for real-time speech to text, speech translation, and batch transcription.
A hosted deployment endpoint isn't required to use custom speech with the Batch transcription API. You can conserve resources if the custom speech model is only used for batch transcription. For more information, see Speech service pricing.
Out of the box, speech recognition utilizes a Universal Language Model as a base model that is trained with Microsoft-owned data and reflects commonly used spoken language. The base model is pretrained with dialects and phonetics representing various common domains. When you make a speech recognition request, the most recent base model for each supported language is used by default. The base model works well in most speech recognition scenarios.
An AI system includes not only the technology, but also the people who use it, the people who are affected by it, and the environment in which it's deployed. Read the transparency notes to learn about responsible AI use and deployment in your systems.
Traditional ESL classes provide a great foundation for basic vocabulary, grammar, syntax, and other linguistic features of a language. However, watching videos with captions or subtitles over the audio of native speakers is a great way for ESL students to improve vocabulary, pronunciation, and inflection and pick up on more nuanced features of English, such as slang terms, phrases, and colloquialisms.
In 2009, a study conducted with Dutch ELLs concluded that watching English-language video content with English captions led to high scores after testing for aural word recognition, while watching English videos with Dutch subtitles led to lower scores on those tests. This suggests that reinforcing English speech with English text helps ELLs memorize spoken and written words in the language, leading to stronger vocabulary skills.
In 2016, a study conducted with a group of intermediate Spanish students of English as a foreign language watched an episode of a television show in its original English version with English, Spanish, or no subtitles overlaid. Before and after the viewing, participants took a listening and vocabulary test to evaluate their speech perception and vocabulary acquisition in English, plus a final plot comprehension test. The results of the listening skills tests revealed that after watching the English subtitled version, participants improved these skills significantly more than after watching the Spanish subtitled or no-subtitle versions.
Many Americans have difficulty understanding certain accents and dialects from places like the UK, Ireland, Australia, and other places where English is spoken. So, imagine what ESL learners have to go through in the same scenario.
If an English word was spoken with a Scottish accent, English subtitles usually told the perceiver what that word was, and hence what its sounds were. This made it easier for the students to tune in to the accent.
This means that by adding captions to their videos, English-speaking online video providers on YouTube and elsewhere can attract viewers anywhere in the world who want to improve their language skills and understand as much regionally-varied English as a native speaker.
As cloud technologies continue to help organizations transform at a rapid pace, employees with the necessary cloud skills are in high demand. According to LinkedIn data, cloud computing is the number one hard skill companies need most.
AWS Academy provides higher education institutions with a free, ready-to-teach cloud computing curriculum that prepares students to pursue industry-recognized certifications and in-demand cloud jobs. Our curriculum helps educators stay at the forefront of AWS Cloud innovation so that they can equip students with the skills they need to get hired in one of the fastest-growing industries.
AWS Academy offers courses and learning resources that enable students to develop a range of skills in the AWS Cloud. Approved educators have access all AWS Academy courses and AWS Academy Learner Lab.
This introductory course is designed to give an overview of how AWS services and cloud computing can be used to solve real-world problems in a variety of industries. Through this course, students will gain a better understanding of the importance of cloud computing skills in many job roles and receive a high-level introduction to numerous AWS services.
This introductory course is intended for students who seek an overall understanding of cloud computing concepts, independent of specific technical roles. It provides a detailed overview of cloud concepts, AWS core services, security, architecture, pricing, and support.
In this introductory course, students will explore AWS services and technologies, and how they can support businesses across the globe. Students will also learn to build on the AWS Management Console, examine successful cloud implementations, and apply their knowledge to cloud-based scenarios.
Extending upon the concepts from AWS Academy Introduction to Cloud: Semester 1, students will continue to explore cloud computing services, applications, and use cases. Students will dive deeper into cloud computing best practices and learn how the cloud helps users develop a global infrastructure at scale by leveraging innovative technologies.
This intermediate-level course will help students gain technical expertise in development with cloud technologies. It will also help them prepare for the AWS Certified Developer - Associate certification exam. Upon completion, students will be able to develop with the AWS SDK and identify best practices for building and deploying applications in the AWS Cloud. This course contains approximately 40 hours of content delivered through lectures and hands-on labs.
This introductory course introduces students to the concepts and terminology of artificial intelligence (AI) and machine learning (ML). By the end of this course, students will be able to select and apply ML services to resolve business problems. They will also be able to label, build, train, and deploy a custom ML model. This course contains approximately 20 hours of content delivered through lectures, hands-on labs, and project work.
This intermediate-level course is designed for students who are pursuing careers that require machine learning knowledge. Students will learn how to describe the terms in the natural language processing (NLP) ecosystem; identify how to use NLP in business; and indicate the range of problems, tasks, and solutions with NLP.
AWS Academy Data Engineering is designed to help students learn about and get hands-on practice with the tasks, tools, and strategies used to collect, store, prepare, analyze, and visualize data for use in analytics and machine learning applications. Throughout the course, students will explore use cases from real world applications that will enable them to make informed decisions while building the data pipeline for their particular application.
This course is designed to help students develop technical expertise in data center operations. Although this is a foundational course, students should possess a general knowledge of mechanical and electrical engineering concepts.
This course is designed to help students gain a foundational knowledge of cybersecurity principles and services for cloud computing through a guided hands-on approach. This course includes demonstrations, instructional guides, and real-life scenarios.
In this project, students are challenged to use AWS services to build a data analytics pipeline to analyze website clickstream data without step-by-step guidance. The pipeline must reflect the principles of the AWS Well-Architected Framework and be able to ingest, transform, analyze, and visualize data to produce meaningful insights for businesses to make informed decisions. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.
In this project, students are challenged to use AWS services to design and deploy a database-backed web application in the AWS Cloud without step-by-step guidance. The architecture must reflect the principles of the AWS Well-Architected Framework and be highly available, scalable, high performing, and secure. Specific sections of the assignment are meant to challenge students on skills that they have acquired throughout the learning process.