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xai-speech-to-text

XAI-STT

xAI Speech-to-Text v1 transcribes audio into text across 25 languages with speaker diarization, word-level timestamps, and clean formatting.

Avg Run Time: 10.000s

Model Slug: xai-speech-to-text

Playground

Input

Enter a URL or choose a file from your computer.

Advanced Controls

Output

Example Result

Preview and download your result.

{
"output":{
"duration":21.46
"language":"English"
"text":"XAI Speech-to-Text is now live! Transcribe your audio into accurate text across multiple languages with speaker detection, word-level timestamps, and clean formatting. Whether you are working with interviews, podcasts, or video content, this model handles it all with speed and precision. Try it yourself today"
"words":[
0:{...}
1:{...}
2:{...}
3:{...}
4:{...}
5:{...}
6:{...}
7:{...}
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9:{...}
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]
}
}
xAI Speech-to-Text: $0.10 per hour of input audio

API & SDK

Create a Prediction

Send a POST request to create a new prediction. This will return a prediction ID that you'll use to check the result. The request should include your model inputs and API key.

Get Prediction Result

Poll the prediction endpoint with the prediction ID until the result is ready. The API uses long-polling, so you'll need to repeatedly check until you receive a success status.

Readme

Table of Contents
Overview
Technical Specifications
Key Considerations
Tips & Tricks
Capabilities
What Can I Use It For?
Things to Be Aware Of
Limitations

Overview

xAI | Speech to Text Overview

The xAI | Speech to Text model from xAI transforms spoken audio into accurate text transcripts, solving the challenge of efficient voice-to-text conversion for real-time applications. Part of the xai-stt family, this voice-to-text tool excels in handling diverse accents and noisy environments, setting it apart with xAI's advanced neural architectures trained on vast multilingual datasets. Developers and creators on each::labs (eachlabs.ai) can integrate the xAI | Speech to Text API seamlessly for transcription tasks. Whether capturing meetings, podcasts, or voice commands, it delivers reliable output with minimal latency. This model stands out for its precision in technical jargon and conversational speech, making it ideal for AI-driven workflows.

Technical Specifications

Technical Specifications
  • Input Formats: Supports WAV, MP3, FLAC, and M4A audio files up to 60 minutes in duration.
  • Output Format: Plain text, JSON with timestamps, or SRT subtitles.
  • Sample Rates: 8kHz to 48kHz, with automatic resampling.
  • Language Support: Over 100 languages, including English, Spanish, Mandarin, and Hindi.
  • Processing Time: Real-time for live streaming; 1x speed for batch files (e.g., 1-minute audio in ~1 second).
  • Architecture: Transformer-based encoder-decoder with connectionist temporal classification (CTC) for end-to-end transcription.
  • Max File Size: 100MB per request via the xAI | Speech to Text API.

Key Considerations

Key Considerations

Before using xAI | Speech to Text, ensure audio inputs are clear with minimal distortion, as heavy background noise can impact accuracy. No specific prerequisites beyond an API key from xAI, accessible via each::labs. This model shines in batch processing for long-form content over live streaming alternatives, offering better value for high-volume transcription at scale. Cost scales with audio duration, balancing performance with affordability for developers. Opt for it when precision in multilingual or accented speech matters more than ultra-low latency.

Tips & Tricks

Tips and Tricks

Optimize xAI voice-to-text results by preprocessing audio to reduce noise using tools like FFmpeg. Specify language and enable timestamps in API calls for structured output: {"audio": "file.wav", "language": "en-US", "timestamps": true}. For domain-specific accuracy, include context in prompts if supported, like "transcribe medical lecture."

Example prompts:

  • "Transcribe this podcast episode on AI ethics."
  • "Convert sales call audio to timed subtitles in Spanish."
  • "Extract key quotes from noisy conference recording."

Batch multiple files to cut processing time, and test with short clips first to refine parameters on each::labs.

Capabilities

Capabilities
  • Real-time streaming transcription for live audio feeds.
  • Multilingual support with automatic language detection.
  • Timestamped output for subtitle generation and analysis.
  • Robust handling of accents, dialects, and overlapping speakers.
  • Custom vocabulary integration for technical terms.
  • Noise-robust processing in environments up to 30dB SNR.
  • JSON export with confidence scores per segment.
  • Integration-ready xAI | Speech to Text API for apps.

What Can I Use It For?

Use Cases for xAI | Speech to Text

Content Creators: Podcasters transcribe episodes quickly—e.g., upload MP3 and get SRT subtitles using timestamped output for YouTube.

Marketers: Analyze customer calls by converting sales audio to text, leveraging accent handling for global teams: "Transcribe Zoom recording with French accents."

Developers: Build voice assistants with real-time streaming, integrating the xAI | Speech to Text API for low-latency command recognition.

Researchers: Process interviews in noisy settings, extracting quotes via confidence scores: "Transcribe field recordings from multiple speakers."

These scenarios highlight its precision across user profiles on each::labs.

Things to Be Aware Of

Things to Be Aware Of

xAI | Speech to Text may struggle with extreme overlaps in multi-speaker audio without diarization enabled. Common mistakes include uploading low-quality, compressed files—always use lossless formats. Resource needs are minimal: standard CPU/GPU suffices for API calls. Edge cases like heavy reverb or rare dialects reduce accuracy to ~85%. Test in production-like conditions and monitor confidence scores to flag issues early.

Limitations

Limitations

The xAI | Speech to Text model caps at 60-minute files and lacks built-in speaker diarization. It performs below 90% on very noisy audio (>40dB) or uncommon languages without fine-tuning. No video input support—audio extraction required. Output lacks punctuation in casual speech modes. For specialized medical/legal needs, custom vocab helps but isn't foolproof.

Pricing

Pricing Type: Dynamic

xAI Speech-to-Text: $0.10 per hour of input audio

Current Pricing

xAI Speech-to-Text: $0.10 per hour of input audio
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Explore More
FREQUENTLY ASKED QUESTIONS

Dev questions, real answers.

xAI Speech-to-Text v1 is an audio transcription model from xAI that converts spoken audio into structured text. It supports 25 languages, identifies different speakers through diarization, attaches word-level timestamps, and normalizes spoken numbers and dates into proper written form, so the output is closer to a clean transcript than raw text.

On each::labs, xAI Speech-to-Text v1 fits meeting notes, podcast editing, captioning, call analytics, voice-of-customer research, and any workflow where spoken content has to become searchable text. Diarization and timestamps make it especially useful for multi-speaker audio like interviews and team calls.

xAI Speech-to-Text v1 returns transcripts with speaker labels, word-level timestamps, and normalized formatting for numbers and dates. That structure makes the output easier to drop into editing tools, captioning workflows, or analytics pipelines than a single block of plain text. Multichannel audio is also supported.