ElevenLabs Speech to Text - Scribe V2

Transcribe audio with speaker identification, timestamps, and multilingual support.

Input Audio

Transcription

"Hey, this is a test recording for Scribe version two, which is now available on jaiportal.com"

Create AI audio in seconds

3,200+ audio files generated this month

📄 About ElevenLabs Speech to Text - Scribe V2

ElevenLabs Speech to Text - Scribe V2 is a cutting-edge AI model designed for rapid, accurate, and insightful audio transcription. Utilizing advanced speech recognition technology, Scribe V2 goes beyond simple transcription by offering speaker diarization, audio event tagging, and word-level timestamps, making it a robust solution for professionals seeking high-quality speech-to-text conversion. This model delivers blazingly fast transcription speeds, ensuring that your audio files are converted to readable text in just seconds. One of the standout features of Scribe V2 is its comprehensive multilingual support. With compatibility for over 70 languages, including English, Spanish, French, German, Japanese, Chinese, Arabic, Hindi, and many more, it serves global businesses, researchers, and content creators who require flexible language processing. The model accepts audio files via direct upload or URL, providing seamless integration into diverse workflows. Scribe V2’s speaker diarization capability allows users to easily identify and annotate individual speakers throughout their recordings. This is especially beneficial for transcribing meetings, interviews, podcasts, and conference calls, where distinguishing between speakers is essential for clarity and accuracy. In addition, the model can automatically tag audio events such as laughter, applause, and other non-verbal cues, offering richer and more contextualized transcripts for analysis or publication. For users who need specialized vocabulary recognition, Scribe V2 features a "keyterms" option, allowing you to bias the model toward up to 100 custom words or phrases. This ensures technical terms, brand names, or industry-specific jargon are accurately captured, making it ideal for legal, medical, academic, or enterprise contexts. The model is highly customizable and user-friendly, with simple controls for language selection, speaker diarization, and event tagging. Scribe V2 is perfect for a range of applications, from media production and journalism to education, customer service, and research. Whether you need quick meeting notes, detailed content from podcasts, or accurate transcripts for accessibility, Scribe V2 offers a powerful and reliable solution. With its pay-as-you-go credit system, you only use resources as needed, making it a cost-effective choice for both occasional and high-volume transcription needs. In summary, ElevenLabs Speech to Text - Scribe V2 redefines audio transcription by combining speed, accuracy, and advanced features in a single, easy-to-use model. Its multilingual capabilities, speaker identification, audio event tagging, and custom vocabulary support make it an indispensable tool for anyone looking to transform audio into actionable, high-quality text.

✨ Key Features

Ultra-fast speech-to-text transcription with rapid turnaround times.

Supports over 70 languages and dialects for truly global coverage.

Speaker diarization automatically identifies and labels individual speakers.

Audio event tagging detects non-verbal events like laughter and applause.

Provides word-level timestamps for detailed transcript analysis.

Custom vocabulary biasing allows for accurate recognition of key terms and brand names.

Flexible input options with support for audio file uploads or URLs.

💡 Use Cases

⚡Transcribing interviews, podcasts, or multi-speaker discussions with speaker identification.

⚡Generating meeting notes or conference transcripts with audio event annotations.

⚡Creating subtitles or captions for video and multimedia content in multiple languages.

⚡Academic research requiring accurate, timestamped transcription of focus groups or lectures.

⚡Legal or medical professionals needing precise transcripts with technical terminology.

⚡Media production workflows that demand fast, reliable speech-to-text conversion.

⚡Enhancing accessibility for hearing-impaired audiences through detailed, event-rich transcripts.

🎯 Best For

🎯 Media professionals, researchers, educators, content creators, and businesses needing fast, accurate, and multilingual speech-to-text transcription.

👍 Pros

✓Delivers transcription results in seconds for increased productivity.

✓Multilingual support covers a wide range of global use cases.

✓Speaker diarization and audio event tagging enrich transcript quality.

✓Custom vocabulary ensures industry-specific accuracy.

✓User-friendly interface with flexible audio input options.

✓Scalable for both small and large transcription workloads.

⚠️ Considerations

△Requires clear audio quality for optimal results.

△Custom vocabulary bias increases processing cost.

△Some languages may have varying levels of accuracy depending on audio conditions.

△Integration with external tools may require additional setup.

📚 How to Use ElevenLabs Speech to Text - Scribe V2

Prepare your audio file or obtain a direct audio URL for the content you want to transcribe.

Upload the audio file or paste the URL into the input field.

Select the language of the audio or leave it on auto-detect for automatic recognition.

Choose whether to enable speaker diarization and audio event tagging as needed.

Optionally, enter custom key terms to improve recognition of specific words or phrases.

Submit your request and receive a detailed, speaker-labeled transcript with event tags and timestamps.

💡 Pro Tips for ElevenLabs Speech to Text - Scribe V2

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Pre-Process Audio for Optimal Accuracy Clean audio yields better transcription results. Remove background noise, normalize volume levels, and ensure speakers are clearly audible before uploading. For recordings with heavy background interference, consider using audio editing software to enhance voice clarity. Scribe V2 performs best with audio where speech is at least 10-15 dB above ambient noise. If you're working with multiple recordings that need consistent quality, establishing a standard recording setup will significantly improve transcription accuracy across your projects.

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Use Language Codes for Faster Processing While auto-detect works well, manually selecting the correct language code speeds up processing and improves accuracy, especially for less common languages or mixed-language content. If your audio contains technical terminology in English but speakers have non-native accents, selecting 'eng' ensures the model prioritizes English vocabulary. For multilingual projects where you need consistent formatting, consider splitting audio by language and processing separately, then combining transcripts. This approach works better than relying on auto-detection for code-switched conversations.

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Leverage Keyterms for Technical Content When transcribing specialized content, add up to 100 custom keyterms to ensure proper recognition of brand names, technical jargon, or uncommon terminology. Format keyterms as a JSON array with exact spelling and capitalization you want preserved. This feature increases cost by 30% but dramatically improves accuracy for industry-specific vocabulary. For medical, legal, or scientific transcriptions, compile a standard keyterms list from your domain to reuse across projects. This investment pays off when accuracy of specialized terms is critical for downstream use.

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Enable Diarization for Multi-Speaker Content Speaker diarization automatically labels who is speaking throughout your recording, essential for interviews, meetings, or panel discussions. The feature works best when speakers have distinct vocal characteristics and don't overlap frequently. For optimal results, ensure speakers take turns clearly and avoid simultaneous speech. If you need to combine transcription with voice generation, consider pairing Scribe V2 with Google Gemini 2.5 Pro Text to Speech to create synthetic versions of transcribed content with different voice profiles matching your original speakers.

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Utilize Audio Event Tags for Rich Context Audio event tagging captures non-verbal cues like laughter, applause, music, and background sounds, adding valuable context to transcripts. This feature is particularly useful for podcast editing, focus group analysis, or creating accessible content where emotional tone matters. Enable this option when transcribing entertainment content, customer service calls, or educational materials where audience reactions provide insight. The tags appear inline with timestamps, making it easy to locate specific moments. For video projects requiring synchronized audio descriptions, these event markers help editors place visual cues accurately.

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Compare with Nemotron for Cost Optimization For straightforward English transcription without speaker identification needs, Nemotron ASR offers a cost-effective alternative. Scribe V2 excels when you need multilingual support, speaker diarization, or audio event detection. Evaluate your project requirements: if you're transcribing single-speaker English podcasts or voiceovers, Nemotron may suffice. For multi-speaker international content, interviews, or recordings where identifying who spoke when matters, Scribe V2's advanced features justify the investment. Run test batches with both models to determine which offers the best value for your specific workflow.

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Frequently Asked Questions

ElevenLabs Scribe V2 supports over 70 languages and dialects, including major global languages such as English, Spanish, French, Chinese, Arabic, and more. This makes it suitable for international transcription needs.

Speaker diarization is the process of identifying and labeling individual speakers within an audio file. This feature helps users distinguish who said what in multi-speaker recordings like meetings, interviews, or podcasts.

Yes, by using the keyterms feature, you can bias the model towards up to 100 custom words or phrases. This is particularly useful for ensuring accurate transcription of technical jargon, brand names, or uncommon terms.

Pricing varies by model and is based on a pay-as-you-go credit system. This allows users to pay only for the resources they consume without any long-term commitments.

The model accepts a wide range of audio formats via file upload or URL, making it flexible for various recording sources and compatible with standard audio types.

Credit usage for Scribe V2 scales with audio duration and selected features. Base transcription costs depend on the length of your audio file, typically calculated per minute. Enabling speaker diarization adds computational overhead but is included in standard pricing. However, using the keyterms feature to bias recognition toward specific vocabulary increases total cost by approximately 30% due to the additional processing required. Audio event tagging is included without extra charge. For budget planning, test with a representative sample first to understand your typical credit consumption. Longer files and multiple advanced features will consume more credits, so consider splitting very long recordings into manageable segments if you're working with limited credits.

Yes, all transcripts generated through JAI Portal using paid credits come with commercial-use rights. This means you can use the output for business purposes including client deliverables, published content, product documentation, marketing materials, and revenue-generating projects. There are no additional licensing fees or attribution requirements for commercial use. This makes Scribe V2 suitable for professional transcription services, media production companies, corporate communications, and content creators monetizing their work. However, you remain responsible for ensuring your input audio doesn't violate copyright or privacy laws. The commercial rights apply to the AI-generated transcript itself, not to any underlying copyrighted audio content you transcribe.

Scribe V2 handles audio files of varying lengths, though practical limits exist based on file size and processing resources. Most users successfully transcribe files ranging from a few seconds to several hours. For very long recordings like full-day conferences or extended interviews, consider splitting audio into manageable segments of 30-60 minutes. This approach offers several advantages: faster processing times, easier error recovery if issues occur, and more manageable transcript files for editing and review. The model processes each segment independently, maintaining consistent quality throughout. If you're working with multi-hour content regularly, establish a workflow that automatically segments audio at natural break points like speaker changes or topic transitions for optimal results.

Both Scribe V2 and Nemotron ASR deliver high accuracy for English transcription, but they excel in different scenarios. Nemotron ASR specializes in English-only content and may offer slightly faster processing for straightforward single-speaker recordings. Scribe V2 provides comparable English accuracy while adding multilingual support, speaker diarization, and audio event tagging. For English podcasts or voiceovers without multiple speakers, both perform excellently. Scribe V2 becomes the clear choice when you need to identify speakers, detect audio events, or handle accented English with custom vocabulary. Accuracy for both models depends heavily on audio quality—clear recordings with minimal background noise yield 95%+ accuracy, while noisy environments or heavy accents may reduce precision to 85-90%.

Yes, Scribe V2 works well in automated transcription pipelines through JAI Portal's API access. You can programmatically submit multiple audio files, monitor processing status, and retrieve completed transcripts without manual intervention. This enables batch processing scenarios where you need to transcribe dozens or hundreds of files efficiently. Set up workflows that automatically transcribe uploaded recordings, process podcast episodes as they're published, or handle customer service call recordings at scale. The model's support for audio URLs makes it easy to integrate with cloud storage systems—simply pass the URL of an audio file stored in your S3 bucket or CDN. For high-volume users, consider implementing retry logic and error handling to manage occasional processing delays or failures gracefully.

⚖️ How ElevenLabs Speech to Text - Scribe V2 Compares

ElevenLabs Speech to Text - Scribe V2 stands out among JAI Portal's transcription models for its comprehensive feature set combining multilingual support, speaker identification, and audio event detection. When compared to Nemotron ASR, Scribe V2 offers significantly broader language coverage with 70+ supported languages versus Nemotron's English focus, making it the go-to choice for international content or multilingual teams. The speaker diarization capability sets Scribe V2 apart for interviews, meetings, and multi-speaker recordings where identifying who said what is essential—a feature Nemotron doesn't provide. For users building complete audio workflows, Scribe V2 integrates well with voice generation models like Google Gemini 2.5 Pro Text to Speech or Qwen 3 TTS, enabling transcribe-edit-regenerate pipelines for content localization or accessibility. Choose Scribe V2 when you need advanced features like custom vocabulary biasing, audio event tagging, or word-level timestamps for detailed analysis. Opt for Nemotron when you're working exclusively with English content and don't require speaker identification, as it may offer faster processing. For projects involving both transcription and music generation, JAI Portal's unified credit system lets you seamlessly combine Scribe V2 with models like ElevenLabs Music Generator for comprehensive audio production. Compare models side-by-side at JAI Portal or start transcribing immediately with pay-as-you-go credits—no subscription required.