Speech-to-Text Rest API

Synchronous Processing

Process short audio files with immediate response. Best for quick transcriptions and testing with a maximum duration of 30 seconds.

Saaras v3: State-of-the-Art Speech Recognition (Recommended)

Saaras v3 is our latest state-of-the-art speech recognition model with flexible output formats. It supports multiple modes for different use cases: transcribe, translate, verbatim, transliterate, and codemix.

Output Modes

Code Examples for Saaras v3

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from sarvamai import SarvamAI
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client = SarvamAI(
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    api_subscription_key="YOUR_SARVAM_API_KEY",
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)
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# Transcribe mode (default)
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response = client.speech_to_text.transcribe(
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    file=open("audio.wav", "rb"),
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    model="saaras:v3",
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    mode="transcribe"  # or "translate", "verbatim", "translit", "codemix"
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)
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print(response)

Legacy Models (Deprecated Soon)

Saarika v2.5: Speech to Text Transcription

Saarika is a speech-to-text transcription model that excels in handling multi-speaker content, mixed language content, and conference recordings.

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from sarvamai import SarvamAI
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client = SarvamAI(
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    api_subscription_key="YOUR_SARVAM_API_KEY",
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)
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response = client.speech_to_text.transcribe(
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    file=open("audio.wav", "rb"),
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    model="saaras:v3",
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    mode="transcribe",
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    language_code="hi-IN"
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)
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print(response)

Saaras v2.5: Speech to Text Translation

Saaras v2.5 is available in the Speech-to-Text Translate endpoint for translating speech directly to English.

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from sarvamai import SarvamAI
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client = SarvamAI(
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    api_subscription_key="YOUR_SARVAM_API_KEY",
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)
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response = client.speech_to_text.translate(
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    file=open("audio.wav", "rb"),
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    model="saaras:v3",
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    mode="translate"
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)
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print(response)

API Response Format

Speech to Text Transcription Response

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{
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  "request_id": "20241115_12345678-1234-5678-1234-567812345678",
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  "transcript": "नमस्ते, आप कैसे हैं?",
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  "language_code": "hi-IN"
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}

Speech to Text Translation Response

Supported source languages: hi-IN, bn-IN, kn-IN, ml-IN, mr-IN, od-IN, pa-IN, ta-IN, te-IN, gu-IN, en-IN

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{
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  "request_id": "20241115_12345678-1234-5678-1234-567812345678",
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  "transcript": "Hello, how are you?",
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  "language_code": "hi-IN"
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}

Error Responses

All errors return a JSON object with an error field containing details about what went wrong.

Error Response Structure

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{
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  "error": {
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    "message": "Human-readable error description",
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    "code": "error_code_for_programmatic_handling",
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    "request_id": "unique_request_identifier"
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  }
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}

Error Codes Reference

Example Error Response

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{
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  "error": {
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    "message": "Unsupported audio format. Supported formats: WAV, MP3, AAC, FLAC, OGG",
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    "code": "unprocessable_entity_error",
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    "request_id": "20241115_abc12345"
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  }
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}

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from sarvamai import SarvamAI
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from sarvamai.core.api_error import ApiError
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client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
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try:
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    response = client.speech_to_text.transcribe(
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        file=open("audio.wav", "rb"),
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        model="saaras:v3",
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        mode="transcribe"
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    )
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    print(response.transcript)
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except ApiError as e:
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    if e.status_code == 400:
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        print(f"Bad request: {e.body}")
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    elif e.status_code == 403:
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        print("Invalid API key. Check your credentials.")
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    elif e.status_code == 429:
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        print("Rate limit exceeded. Wait and retry.")
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    elif e.status_code == 503:
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        print("Service overloaded. Retry with backoff.")
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    else:
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        print(f"Error {e.status_code}: {e.body}")

Next Steps