AI transcription converts spoken language into written text using AI and machine learning. An AI transcription model powers this process, and its quality and size determine accuracy, context, adaptability, language support, and noise handling.
Let's explore the AI model variations from OpenAI's transcription software Whisper, which serves as the core model for the VocalStack platform:
| Model | Parameters | Transcription Quality |
|---|---|---|
| Whisper Tiny | 39 Million | Limited |
| Whisper Base | 74 Million | Moderate |
| Whisper Small | 244 Million | Good |
| Whisper Medium | 769 Million | Very Good |
| Whisper Large-v3 | 1.55 Billion | Excellent |
Parameters are the internal settings of an AI model that adjust during training, allowing the model to learn patterns in the data, such as recognizing different languages, accents, and contexts. More parameters mean the model can capture these details more effectively, leading to higher quality and more accurate transcriptions.
To better understand the impact of an AI model's size, let's use the different Whisper models to transcribe an example of some speech:
80%
DifferenceRaw Text
DifferenceIn a quaint little cafée near the Thames, Claire chuckled as Pierre ate eight eclairs all in one go. Anticipating gastroeisophageal reflux, he said, "nope, they're not worth it!". Later, they called a Lylift to drive them to the park, as Pierre thinks it's cheaper than Uber. As they walked under the glow of the noctialucent sky, they jumped when they'd seen a bear clothed only in his beare fur. Pierre cried out loud, "Mon Dideu!". They both leapt hastily into the river and swam for Chiswick Eyoat. Phewoo!
Original Text
In a quaint little café near the Thames, Claire chuckled as Pierre ate eight eclairs all in one go. Anticipating gastroesophageal reflux, he said "nope, they're not worth it!" Later, they called a Lyft to drive them to the park, as Pierre thinks its cheaper than Uber. As they walked under the glow of the noctilucent sky, they jumped when they'd seen a bear clothed only in his bare fur. Pierre cried out loud, "Mon Dieu!" They both leapt hastily into the river and swam for Chiswick Eyot. Phew!
A good transcription model offers more than just basic text output. Here are key qualities to look for:
- Accuracy! - Inaccurate transcriptions can lead to misunderstandings. This happens especially when the AI creates complete sentences that seem correct at first glance but don't accurately reflect what was said in the audio.
- Contextual Understanding - Advanced models understand homophones (words that sound the same but have different meanings) based on the context in which they're used. For example, the words 'bare' and 'bear' in English sound identical but have completely different meanings, and a transcription model must understand the context to choose the correct word. This also includes recognizing and correctly formatting entities like dates, times, and proper nouns.
- Language and Accent Support - High-quality models support a wide range of languages and accents, making transcription services accessible to a global user base. This inclusivity expands the potential applications of AI transcription services and ensures that non-native speakers or individuals with strong regional accents are accurately represented.
- Handling Noisy Environments - Transcribing speech accurately in noisy environments or with background sounds is challenging. Less-than-ideal recording conditions can include live events or in busy office settings. Larger, more advanced AI models are often better equipped with noise-reduction technologies and can effectively isolate the speaker's voice from unwanted background noise.
- Adaptability - A good model can adapt to specific terminology used in different domains such as medical, legal, or technical fields. This adaptability improves the transcription's relevance and usefulness to professionals in those areas by accurately capturing specialized vocabulary.
We've discussed the advantages of using large AI models for transcription and the challenges they bring. While large models offer superior quality, accuracy, and contextual understanding, they come with increased costs, hardware requirements, and the challenges involved in implementing a custom solution to ensure fast transcription performance.
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Many SaaS transcription services typically do not disclose which AI models they use, often because they are attempting to cut costs by avoiding large, resource-intensive models. Instead, they may use smaller models to reduce infrastructure costs, sacrificing some accuracy and versatility in the process.
If you're convinced that large models are essential for delivering the best transcription results, it's crucial to find practical ways to make their implementation viable for your business. That's where VocalStack comes in—providing solutions that make it easier to leverage advanced AI models without having to worry about infrastructure complexity or exorbitant costs.
Read more here https://www.vocalstack.com/business
VocalStack provides both pre-recorded and live transcription services at a reasonable price. Additionally, at no extra cost, VocalStack leverages a diverse range of AI models to enhance the quality of each transcription, including:
- Summarization - Generating concise summaries of the transcription.
- Key Words - Identifying key topics and phrases from the transcription.
- Paragraph Segmentation - Structuring text into readable paragraphs.
- Word Level Timestamps - Providing precise timestamps for each word to help track content accurately.
Large AI models are transforming the way we interact with speech-to-text technology. Platforms like VocalStack leverage these advanced models to deliver precise, real-time, and multilingual transcriptions, with additional layers of contextual understanding and post-processing. Whether it's ensuring flawless grammar, supporting 57 languages, or adapting to specialized terminology, the role of large AI models is irreplaceable.
For anyone looking to integrate cutting-edge speech-to-text solutions, the choice is clear—large AI models provide the reliability, accuracy, and versatility needed to make transcriptions not just possible, but powerful.
Ready to experience next-level transcription? Visit VocalStack today and see how AI can transform your spoken words into actionable, fluent text.
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