> ## Documentation Index
> Fetch the complete documentation index at: https://docs.simplismart.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Transcription Models

> Get real-time, high-quality speech-to-text output for any audio with fast STT processing, live results, and support for various audio formats.

The Whisper playground is designed for audio processing and transcription. You can:

* **Upload Audio Files**: Test the model by uploading audio files and receiving transcriptions.
* **Set Advanced Parameters**: Configure settings such as initial prompts, the number of speakers, beam size, audio sample rate, and more to fine-tune transcription accuracy.
* **Process Audio Real-Time**: Experience real-time audio processing and transcription to evaluate performance in various scenarios.
* **Evaluate Results**: Review and analyze transcriptions to ensure they meet the desired accuracy and quality.

### <img src="https://mintcdn.com/simplismart-3f10d72e/gTRCmRuan7ftye2b/images/Whisper_Playground_1.webp?fit=max&auto=format&n=gTRCmRuan7ftye2b&q=85&s=8be74bf8013bd9663bd7e13ba56fc828" alt="Whisper" width="2304" height="1207" data-path="images/Whisper_Playground_1.webp" />

***

### **Settings explained**

`language`: Language spoken in the audio, specify None to perform language detection.

`task`: Determines if the Whisper model should perform translation or transcription.

`initial prompt`: Optional starting text prompt for the model, useful for guiding the initial context. e.g. custom vocabularies or proper nouns to make it more likely to predict those word correctly.

`best of`: Specifies how many decoding paths to consider and choose the best from, higher values can improve quality.

`no of speakers`: The number of speakers in the audio, important for separating dialogues.

`diarization`: Assignment of speakers to different parts of the text.

`word timestamps`: Indicates if word-level timestamps should be in the output.

`without timestamps`: Option to exclude timestamps in the output.

`beam size`: Controls the breadth of search in beam search decoding, larger values improve accuracy but increase computation.

`length penalty`: A factor that penalizes longer predictions, helps control output length.

`batch size`: The number of audio samples processed together in one batch.

`patience`: The duration to wait before making a prediction, useful for adjusting responsiveness.

`minimum duration on`: Minimum duration of speech to consider it as an active segment.

`minimum duration off`: Minimum duration of silence to consider it as a break.

`maximum duration`: The longest duration of speech to process in one go, prevents excessive processing time.

`maximum speakers`: The maximum number of speakers expected in the audio.

`minimum speakers`: The minimum number of speakers expected in the audio.

`vad onset`: Sensitivity for detecting the start of speech.

`vad offset`: Sensitivity for detecting the end of speech.

`pad onset`: Additional padding time added to the start of detected speech.

`pad offset`: Additional padding time added to the end of detected speech.

***

<Info>
  Access the Whisper model API documentation [here](/api-reference/inference/whisper-v3) for endpoints, parameters, and code examples.
</Info>

<Tip>
  Need help with VAD parameter tuning or Whisper troubleshooting? Check our detailed guides on [VAD tuning](/troubleshooting-faq/vad-parameter-tuning) and [Whisper troubleshooting](/troubleshooting-faq/whisper-troubleshooting).
</Tip>

***

### Supported Languages with their Codes

```json theme={null}
LANGUAGES =  {
    "en": "english",
    "zh": "chinese",
    "de": "german",
    "es": "spanish",
    "ru": "russian",
    "ko": "korean",
    "fr": "french",
    "ja": "japanese",
    "pt": "portuguese",
    "tr": "turkish",
    "pl": "polish",
    "ca": "catalan",
    "nl": "dutch",
    "ar": "arabic",
    "sv": "swedish",
    "it": "italian",
    "id": "indonesian",
    "hi": "hindi",
    "fi": "finnish",
    "vi": "vietnamese",
    "he": "hebrew",
    "uk": "ukrainian",
    "el": "greek",
    "ms": "malay",
    "cs": "czech",
    "ro": "romanian",
    "da": "danish",
    "hu": "hungarian",
    "ta": "tamil",
    "no": "norwegian",
    "th": "thai",
    "ur": "urdu",
    "hr": "croatian",
    "bg": "bulgarian",
    "lt": "lithuanian",
    "la": "latin",
    "mi": "maori",
    "ml": "malayalam",
    "cy": "welsh",
    "sk": "slovak",
    "te": "telugu",
    "fa": "persian",
    "lv": "latvian",
    "bn": "bengali",
    "sr": "serbian",
    "az": "azerbaijani",
    "sl": "slovenian",
    "kn": "kannada",
    "et": "estonian",
    "mk": "macedonian",
    "br": "breton",
    "eu": "basque",
    "is": "icelandic",
    "hy": "armenian",
    "ne": "nepali",
    "mn": "mongolian",
    "bs": "bosnian",
    "kk": "kazakh",
    "sq": "albanian",
    "sw": "swahili",
    "gl": "galician",
    "mr": "marathi",
    "pa": "punjabi",
    "si": "sinhala",
    "km": "khmer",
    "sn": "shona",
    "yo": "yoruba",
    "so": "somali",
    "af": "afrikaans",
    "oc": "occitan",
    "ka": "georgian",
    "be": "belarusian",
    "tg": "tajik",
    "sd": "sindhi",
    "gu": "gujarati",
    "am": "amharic",
    "yi": "yiddish",
    "lo": "lao",
    "uz": "uzbek",
    "fo": "faroese",
    "ht": "haitian creole",
    "ps": "pashto",
    "tk": "turkmen",
    "nn": "nynorsk",
    "mt": "maltese",
    "sa": "sanskrit",
    "lb": "luxembourgish",
    "my": "myanmar",
    "bo": "tibetan",
    "tl": "tagalog",
    "mg": "malagasy",
    "as": "assamese",
    "tt": "tatar",
    "haw": "hawaiian",
    "ln": "lingala",
    "ha": "hausa",
    "ba": "bashkir",
    "jw": "javanese",
    "su": "sundanese",
    "yue": "cantonese",
}
```