VNClagoon AI Research on AI Efficiency: How Intel’s Meteor Lake Powers Whisper for Next-Gen Speech Recognition
In the course of our VNClagoon AI projects, we are testing Whisper to leverage its advanced speech recognition capabilities within our suite of enterprise applications. By integrating Whisper, VNClagoon aims to enhance communication, collaboration, and productivity for users, particularly through accurate multilingual transcription and translation services, helping businesses manage tasks more efficiently with AI-driven tools.
The Intel Meteor Lake CPUs, which were launched in late 2023, represent a significant advancement in processor technology, offering enhanced processing power and superior multitasking capabilities.
Whisper by OpenAI is an open-source automatic speech recognition (ASR) system based on an encoder-decoder model, also referred to as a sequence-to-sequence model. The model will be executed on the CPU, GPU, or NPU (just one of these at a time) for the transcription of audio with high accuracy, including support for multiple languages.
Intel is optimizing Whisper for its Meteor Lake processors by improving the system’s efficiency in handling AI workloads, specifically focusing on maximizing performance while minimizing power consumption. This involves tuning Whisper to take advantage of Meteor Lake’s architectural advancements, such as enhanced processing cores and specialized hardware accelerators, enabling faster and more energy-efficient transcription and translation tasks on CPUs, GPUs, or NPUs.
VNClagoon is an integrated suite of enterprise applications that provides a secure alternative to established software giants. VNClagoon offers a range of solutions designed to help businesses and individuals streamline their workflows, improve communication and collaboration, and enhance their overall productivity. VNC focuses on leveraging the power of AI (Artificial Intelligence) within the VNClagoon environment to provide efficient and secure ways to manage tasks, projects, and other work-related activities.
VNC is using Whisper large-v3 with 1550 M parameters. This multilingual model was trained simultaneously on multilingual speech recognition and speech translation.
For speech recognition, the model predicts transcriptions in the same language as the audio. For speech translation, the model predicts transcriptions to a different language to the audio.
Our evaluation of the performance of Whisper for different languages (EN, DE) involves analyzing how well it transcribes speech across a diverse set of linguistic, phonetic, and grammatical features.
Our findings are that Whisper supports a wide range of languages, including major ones like English and German. Whisper is strong in semantic understanding, including languages with complex grammatical structures (German). We experienced good results in the handling of varied audio quality: transcribe speech from audio files with background noise or low-quality recordings.
Whisper provides high transcription accuracy:
Our Test results are: German 0.15 or 15%, English 0.02 (2%).
In English, the transcription has excellent accuracy and in German, the transcription has some minor errors but is generally very accurate.
Background Info:
The Word Error Rate (WER) is a common metric used to evaluate the accuracy of automatic speech recognition (ASR) systems, like Whisper. It measures how well the system’s transcription matches the reference (or ground truth) transcription. A lower WER indicates better accuracy and better performance, while higher values point to more transcription errors.
Interpretation of WER:
WER < 10%: Excellent accuracy, close to human-level performance.
10% ≤ WER < 30%: Good accuracy, but with some noticeable mistakes.
30% ≤ WER < 50%: Fair accuracy, with significant room for improvement.
WER ≥ 50%: Poor accuracy, likely too many errors to be useful.
Speech to text with Agent Vincent in our VNCtalk test environment
AI Components in VNClagoon
We already embedded several AI components within VNClagoon.
Get a first impression of the AI components in VNClagoon in our short video:
Confidential AI in VNClagoon:
Various components of the AI flow such as the LLM and Vector Store reside on the local Intel Core Ultra (Meteor Lake) system, making Confidential AI possible.
The data themselves are hosted securely within the VNClagoon environment, prompting exclusively the company‘s own data, and access to external sources is only triggered upon explicit request.
Learn more about VNClagoon AI in our blogposts, videos and press releases:
The five key elements of Confidential AI (July 16, 2024)
New VNClagoon AI Demo Video (June 26, 2024)
VNClagoon at Intel Vision EMEA 2024: AI everywhere! (May 16, 2024)
VNC showcases AI-powered secure collaboration at Intel Vision EMEA 2024 (May 07, 2024)
You can also find a series of mini-videos on our VNClagoon youtube Channel.
Detailed information on the VNClagoon Communication & Collaboration Suite can be found at VNClagoon.com.
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About VNClagoon
Secure, first-class, seamless communication and collaboration, lowest TCO
The VNClagoon Enterprise Software Suite offers a comprehensive range of integrated communication and collaboration products for messaging, real-time conferencing, community building, channels, email, groupware, task and project management, file management and much more for large organizations. Based on state-of-the-art open-source technology developed by thousands of developers around the world, VNClagoon is a leading alternative to closed-source and pure SaaS applications such as Microsoft Teams, Zoom, WhatsApp, Dropbox and many others. Now it is possible for VNClagoon customers to gain greater control over their digital sovereignty by communicating and collaborating more securely with a fully integrated suite of applications. More information on https://vnclagoon.com/
