An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
Learn more
LM-Kit.NET is an enterprise-grade toolkit designed for seamlessly integrating generative AI into your .NET applications, fully supporting Windows, Linux, and macOS. Empower your C# and VB.NET projects with a flexible platform that simplifies the creation and orchestration of dynamic AI agents.
Leverage efficient Small Language Models for on‑device inference, reducing computational load, minimizing latency, and enhancing security by processing data locally. Experience the power of Retrieval‑Augmented Generation (RAG) to boost accuracy and relevance, while advanced AI agents simplify complex workflows and accelerate development.
Native SDKs ensure smooth integration and high performance across diverse platforms. With robust support for custom AI agent development and multi‑agent orchestration, LM‑Kit.NET streamlines prototyping, deployment, and scalability—enabling you to build smarter, faster, and more secure solutions trusted by professionals worldwide.
Learn more
MAI-Transcribe-1.5
MAI-Transcribe-1.5 represents Microsoft AI’s advanced speech-to-text solution, expertly converting challenging audio into precise, contextually relevant transcripts in 43 different languages. This model ensures reliable and high-accuracy transcription that accommodates various languages, accents, speaking styles, and difficult audio environments, incorporating automatic language detection for added convenience. It is expertly crafted to handle real-world audio scenarios, such as those found in conference rooms, over phone calls, in bustling streets, and even from low-quality recordings that might include background noise or overlapping dialogue. Furthermore, MAI-Transcribe-1.5 is tailored to understand and utilize domain-specific language, making it incredibly useful for tasks like captioning, call analysis, enhancing accessibility, transcribing meetings, recording doctor’s notes, managing pharma customer interactions, and streamlining content workflows, all without requiring extensive setup. The model leverages contextual biasing to enhance its comprehension of specialized vocabulary, names, and industry-specific jargon that standard transcription systems often overlook, ensuring that users receive the most accurate and relevant transcripts possible. By seamlessly integrating into various enterprise applications, it significantly enhances productivity and communication efficiency in professional settings.
Learn more
MAI-Transcribe-2
MAI-Transcribe-2 represents the pinnacle of Microsoft AI's transcription capabilities, engineered to provide rapid and precise speech recognition across various real-world audio scenarios. This model includes features like speaker diarization, enabling it to differentiate between speakers and correctly attribute dialogue, as well as offering word-level timestamps for enhanced alignment, searching, navigation, and editing purposes. Additionally, it utilizes keyword biasing to improve the recognition of specialized terms, abbreviations, and names that may otherwise be challenging to identify from their contextual usage. Developers are afforded the flexibility to select from different transcription styles: a verbatim option that retains filler words and false starts for thorough analysis and compliance, or a clean option that eliminates such elements for clearer captions and more polished published transcripts. Furthermore, the model is adept at handling code-switching, seamlessly transitioning between languages during conversations, even accommodating mixed language combinations like Hinglish and Spanglish, while automatically identifying the language being spoken. This makes MAI-Transcribe-2 an invaluable tool for diverse linguistic environments and applications.
Learn more