REST

The audio file to transcribe. Supported formats include WAV, MP3, AAC, AIFF, OGG, OPUS, FLAC, MP4/M4A, AMR, WMA, WebM, and PCM formats. The API automatically detects most codec formats, but for PCM files (pcm_s16le, pcm_l16, pcm_raw), you must specify the input_audio_codec parameter. PCM files are supported only at 16kHz sample rate. The API works best with audio files sampled at 16kHz. If the audio contains multiple channels, they will be merged into a single channel.

Specifies the model to use for speech-to-text conversion. - **saaras:v3** (default, recommended): State-of-the-art model with flexible output formats. Supports multiple modes via the `mode` parameter: transcribe, translate, verbatim, translit, codemix. - **saaras:v4** (latest): Flexible output formats across all modes (transcribe, translate, verbatim, translit, codemix), supporting Global + Indian English and 22 Indic languages.

Mode of operation. **Only applicable when using saaras:v3 model.** Example audio: 'मेरा फोन नंबर है 9840950950' - **transcribe** (default): Standard transcription in the original language with proper formatting and number normalization. - Output: `मेरा फोन नंबर है 9840950950` - **translate**: Translates speech from any supported Indic language to English. - Output: `My phone number is 9840950950` - **verbatim**: Exact word-for-word transcription without normalization, preserving filler words and spoken numbers as-is. - Output: `मेरा फोन नंबर है नौ आठ चार zero नौ पांच zero नौ पांच zero` - **translit**: Romanization - Transliterates speech to Latin/Roman script only. - Output: `mera phone number hai 9840950950` - **codemix**: Code-mixed text with English words in English and Indic words in native script. - Output: `मेरा phone number है 9840950950`

Specifies the language of the input audio in BCP-47 format. **Available Options:** - `unknown`: Use when the language is not known; the API will auto-detect. - `hi-IN`: Hindi - `bn-IN`: Bengali - `kn-IN`: Kannada - `ml-IN`: Malayalam - `mr-IN`: Marathi - `od-IN`: Odia - `pa-IN`: Punjabi - `ta-IN`: Tamil - `te-IN`: Telugu - `en-IN`: English - `gu-IN`: Gujarati - `as-IN`: Assamese - `ur-IN`: Urdu - `ne-IN`: Nepali - `kok-IN`: Konkani - `ks-IN`: Kashmiri - `sd-IN`: Sindhi - `sa-IN`: Sanskrit - `sat-IN`: Santali - `mni-IN`: Manipuri - `brx-IN`: Bodo - `mai-IN`: Maithili - `doi-IN`: Dogri

Enables chunk-level timestamps in the response. If set to `true`, the response includes a `timestamps` object with `words`, `start_time_seconds`, and `end_time_seconds` (each entry covers a sentence or phrase, not an individual word). **Note:** Word-level timestamps are not supported. Speaker diarization is not supported on the REST API; use the Batch API for diarized, chunk-level timestamps.

List of up to 50 domain-specific terms (names, places, brands, technical terms) to bias recognition toward. Each keyterm can contain up to 64 characters. Put phrases such as `New Delhi` in one list item; do not send comma-separated terms in one string. Keyterms bias recognition — they do not guarantee that a term will appear in the transcript. **Only supported with `model=saaras:v4`.** Sent as a JSON-encoded array in one multipart form field, e.g. `keyterms=["Sarvam","New Delhi","Vistaar"]`. Do not use the older `keyterm` or `hotwords` fields.