REST and Batch APIs support a wide range of audio formats including:

• WAV
• MP3
• M4A
• AAC
• OGG
• FLAC
• WebM
• PCM (pcm_s16le, pcm_l16, pcm_raw)

WebSocket/Streaming APIs only support:

• WAV
• Raw PCM (pcm_s16le, pcm_l16, pcm_raw)

For optimal results, we recommend:

• Sample rate: 16kHz or higher
• Bit depth: 16-bit
• Channels: Mono or Stereo

Our models support multiple Indian and global languages:

Indian Languages

• Hindi
• English (Indian)
• Bengali
• Tamil
• Telugu
• Kannada
• Malayalam
• Marathi
• Gujarati
• Punjabi

Global Languages

• English (US, UK, AU)
• French
• German
• Spanish
• Japanese

Check our models page for the complete list and specific model capabilities.

The limits vary by API endpoint:

REST API

• Maximum file size: 1GB
• Maximum duration: 4 hours

WebSocket API (Streaming)

• No file size limit
• Maximum continuous stream duration: 8 hours

For longer audio files, we recommend:

1. Splitting into smaller segments
2. Using batch processing
3. Contacting support for custom solutions

Accuracy varies based on several factors:

Typical Accuracy Rates

• Clear speech, minimal background noise: 95-98%
• Multiple speakers, moderate noise: 90-95%
• Heavy accent or background noise: 85-90%

Factors affecting accuracy:

• Audio quality
• Background noise
• Speaker accent
• Speaking speed
• Domain-specific terminology

Use our playground to test with your specific audio.

Speaker diarization identifies and labels different speakers in the audio:

1. Process:

   • Voice activity detection
   • Speaker segmentation
   • Speaker clustering
   • Speaker labeling

2. Usage (via Batch API):

1
from sarvamai import SarvamAI
2
3
client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
4
5
# Speaker diarization is available through the Batch API
6
# See: https://docs.sarvam.ai/api-reference-docs/speech-to-text/batch
7
response = client.speech_to_text.batch_transcribe(
8
    file=open("audio.mp3", "rb"),
9
    model="saaras:v3",
10
    mode="transcribe",
11
    with_diarization=True
12
)

3. Output:

   1
   {
   2
     "segments": [
   3
       {
   4
         "speaker": "Speaker 1",
   5
         "text": "Hello, how are you?",
   6
         "start": 0.0,
   7
         "end": 1.5
   8
       },
   9
       {
   10
         "speaker": "Speaker 2",
   11
         "text": "I'm doing well, thanks!",
   12
         "start": 1.8,
   13
         "end": 3.2
   14
       }
   15
     ]
   16
   }

Rate limits are applied per account based on your subscription plan:

File Size Limits

• REST API: Max 1GB file, up to 4 hours duration
• Streaming API: No file size limit, up to 8 hours continuous

For batch endpoints, implement a minimum 5ms delay between status polling requests.

View the full Credits & Rate Limits page for details on HTTP headers, error handling, and upgrade paths.

Common errors and solutions:

1. Authentication Errors (401)

1
{
2
  "error": "invalid_api_key",
3
  "message": "API key is invalid or expired"
4
}

Solution: Check API key validity and proper configuration

2. Rate Limit Errors (429)

1
{
2
  "error": "rate_limit_exceeded",
3
  "message": "Rate limit exceeded",
4
  "retry_after": 3600
5
}

Solution: Implement exponential backoff or upgrade plan

3. Invalid Input (400)

1
{
2
  "error": "invalid_input",
3
  "message": "Unsupported audio format"
4
}

Solution: Check supported formats and requirements

See our error handling guide for more details.

Tips for optimal real-time performance:

1. Audio Settings

1
const config = {
2
  sampleRate: 16000,
3
  encoding: 'LINEAR16',
4
  channels: 1
5
}

2. Chunk Size

• Optimal: 100ms - 500ms chunks
• Balance between latency and accuracy

3. WebSocket Connection

1
const ws = new WebSocket('wss://api.sarvam.ai/v1/stt/stream')
2
ws.binaryType = 'arraybuffer'

4. Error Handling

1
ws.onerror = (error) => {
2
  console.error('WebSocket Error:', error)
3
  // Implement reconnection logic
4
}

View our real-time guide for detailed examples.

Usage is calculated based on:

1. Audio Duration

• Rounded up to the nearest second
• Minimum charge: 1 second

2. Features Used

• Base transcription
• Speaker diarization (+20%)
• Language detection (+10%)
• Word timestamps (+10%)

3. Model Type

• Saarika: Base rate
• Saaras: Premium rate

Example calculation:

5 minutes audio × Base rate
+ Speaker diarization (20%)
+ Word timestamps (10%)
= Total cost

Multiple support channels available:

1. Documentation

• API Reference
• Guides
• Examples

2. Community

• Discord Community

3. Direct Support

• Email: developer@sarvam.ai
• Enterprise: Dedicated support manager