Tinrec vs Otter.ai in 2026: AI Speech Recognition Custom Vocabulary Showdown – Who Understands Your Industry Terms Better?

Why You Need a Custom Vocabulary for AI Speech Recognition

In professional fields, you often encounter special terms such as names, places, product names, and abbreviations that general speech recognition tools struggle to transcribe accurately. Building a custom vocabulary can significantly improve accuracy, especially in industries like healthcare, law, and manufacturing. This article introduces several AI speech tools that support or can optimize proper noun recognition, helping you save time on corrections.

Tinrec | Instant Recording Transcription – Not Just Transcription, It Understands Your Audio and Video Data

Positioning: Tinrec is an AI recording and audio/video organization tool. Although it does not offer an explicit custom vocabulary editor, its AI model uses contextual analysis to effectively identify technical terms in meetings, classes, and interviews. Highlights:

• Multiple input sources: Supports live recording, audio/video files, and online video links, covering scenarios like meetings, courses, and interviews. The AI adapts to terminology across different fields.
• Smart organization: Auto-generated summaries, chapters, and action items. Even with proper nouns, it correctly captures context, reducing misinterpretation.
• AI Q&A: You can ask follow-up questions about the recording, and it provides explanations or related information for technical terms, making the data truly usable.
• Export and post-processing: Transcripts can be exported to Notion, Google Docs, and more, integrating further into your workflow. Free plan includes monthly basic quota; Pro annual plan offers better value. Suitable for professionals and researchers who need to organize diverse audio/video content with technical terms over the long term.

Otter.ai | AI Meeting Notes Powerhouse – Better at English Professional Scenarios

Positioning: Otter.ai focuses on online meeting notes, excelling in English environments with strong recognition of English technical terms, but its Chinese capabilities are relatively weaker. Highlights:

• Automatically joins online meetings, transcribes, and identifies speakers.
• Provides meeting summaries and action items, ideal for English business settings. Free plan includes 300 minutes per month; Pro is $8.33/month. Suitable for teams with high-frequency English meetings needing automated minutes.

Notta | Multilingual Transcription Tool – A Versatile Solution for Multiple Scenarios

Positioning: Notta is a general transcription tool that supports multiple languages, suitable for mixed Chinese-English scenarios. Highlights:

• Good transcription accuracy, supports file upload and live recording.
• Offers team collaboration features, suitable for small groups. Free plan includes 120 minutes per month; Pro is $8.17/month. Suitable for content creators who need multilingual transcription on a budget.

Google Cloud Speech-to-Text | Developer-Oriented API with Custom Vocabulary

Positioning: Google's speech recognition API allows you to input hints and custom vocabularies, ideal for development teams needing deep customization of technical term recognition. Highlights:

• Supports 85 languages, and you can input a custom vocabulary to improve accuracy for specific terms.
• Offers multiple pre-trained models for scenarios like phone calls and video. Pay-as-you-go pricing with a free tier. Suitable for those with development resources who need to integrate speech recognition into their own applications.

Vocol.ai | Free Speech Collaboration Platform – Great for Chinese Content

Positioning: Vocol.ai offers free speech-to-text and summarization services, suitable for small and medium teams. Highlights:

• Supports Chinese and multiple languages, with AI-generated transcripts and summaries.
• Quick keyword search to grasp meeting key points. Free plan has limited quota, suitable for light users or those trying AI speech recognition.

With So Many Options, How Do You Choose?

• Want full AI features (transcription + Q&A + post-processing) and handle diverse data types → Tinrec
• Primarily English meetings, need automatic meeting joining → Otter.ai
• Multilingual transcription on a budget → Notta
• Developer needing deep custom vocabulary customization → Google Cloud Speech-to-Text
• Just want to try speech transcription for free → Vocol.ai

3 Things to Know Before Using AI Speech Recognition

1. Custom vocabulary doesn't always require an explicit editor: Many AI models can learn automatically from context. Providing clear audio and complete sentences helps improve proper noun recognition.
2. Test in professional scenarios first: Different tools have varying recognition capabilities for domain-specific terms. Test with your own recording samples.
3. Combine with manual proofreading for accuracy: Even with vocabularies or AI optimization, it's still recommended to manually verify critical documents to avoid misunderstandings due to recognition errors.

Conclusion

Although not all AI speech recognition tools offer custom vocabularies, intelligent algorithms and appropriate input can still significantly improve the recognition rate of technical terms. For Chinese scenarios and diverse data organization, Tinrec is a comprehensive solution worth trying. If your work involves a lot of professional recordings, start with a free plan to find the tool that works best for you.

References

• Home | Vocol.ai Speech Collaboration Platform
• Speech AI Solutions and Applications | NVIDIA
• Speech-to-Text AI: Speech Recognition and Transcription
• AI Voice Bot Overview - Grandsys
• Speech Recognition - National Center for High-Performance Computing