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

# Speech Threshold

<Note>
  **Supported Languages, Regions, and Models**

  Speech threshold is supported for all languages, regions, and models.
</Note>

To only transcribe files that contain at least a specified percentage of spoken audio, you can set the `speech_threshold` parameter. You can pass any value between 0 and 1.

If the percentage of speech in the audio file is below the provided threshold, the value of `text` is `None` and the response contains an `error` message:

```plain theme={null}
Audio speech threshold 0.9461 is below the requested speech threshold value 1.0
```

<Warning>
  A file must contain at least 30 seconds of audio for the amount of spoken
  audio to reliably be determined.
</Warning>

<CodeGroup>
  ```python title="Python SDK" highlight={8}  theme={null}
  import assemblyai as aai

  aai.settings.api_key = "<YOUR_API_KEY>"

  # audio_file = "./local_file.mp3"
  audio_file = "https://assembly.ai/wildfires.mp3"

  config = aai.TranscriptionConfig(
      speech_models=["universal-3-pro", "universal-2"],
      language_detection=True,
      speech_threshold=0.5
  )

  transcript = aai.Transcriber(config=config).transcribe(audio_file)

  if transcript.status == "error":
    raise RuntimeError(f"Transcription failed: {transcript.error}")

  print(transcript.text)
  ```

  ```python title="Python" highlight={19}  expandable theme={null}
  import requests
  import time

  base_url = "https://api.assemblyai.com"

  headers = {
      "authorization": "<YOUR_API_KEY>"
  }

  with open("./my-audio.mp3", "rb") as f:
    response = requests.post(base_url + "/v2/upload",
                            headers=headers,
                            data=f)

  upload_url = response.json()["upload_url"]

  data = {
      "audio_url": upload_url, # You can also use a URL to an audio or video file on the web
      "speech_models": ["universal-3-pro", "universal-2"],
      "language_detection": True,
      "speech_threshold": 0.5
  }

  url = base_url + "/v2/transcript"
  response = requests.post(url, json=data, headers=headers)

  transcript_id = response.json()['id']
  polling_endpoint = base_url + "/v2/transcript/" + transcript_id

  while True:
    transcription_result = requests.get(polling_endpoint, headers=headers).json()

    if transcription_result['status'] == 'completed':
      print(f"Transcript ID: {transcript_id}")
      break

    elif transcription_result['status'] == 'error':
      raise RuntimeError(f"Transcription failed: {transcription_result['error']}")

    else:
      time.sleep(3)

  ```

  ```javascript title="JavaScript SDK" highlight={12}  expandable theme={null}
  import { AssemblyAI } from "assemblyai";

  const client = new AssemblyAI({
    apiKey: "<YOUR_API_KEY>",
  });

  // const audioFile = './local_file.mp3'
  const audioFile = "https://assembly.ai/wildfires.mp3";

  const params = {
    audio: audioFile,
    speech_models: ["universal-3-pro", "universal-2"],
    language_detection: true,
    speech_threshold: 0.5,
  };

  const run = async () => {
    const transcript = await client.transcripts.transcribe(params);

    if (transcript.status === "error") {
      throw new Error(`Transcription failed: ${transcript.error}`);
    }

    console.log(transcript.text);
  };

  run();
  ```

  ```javascript title="JavaScript" highlight={19}  expandable theme={null}
  import fs from "fs-extra";

  const baseUrl = "https://api.assemblyai.com";

  const headers = {
    authorization: "<YOUR_API_KEY>",
  };

  const path = "./my-audio.mp3";
  const audioData = await fs.readFile(path);
  let res = await fetch(`${baseUrl}/v2/upload`, {
    method: "POST",
    headers,
    body: audioData,
  });
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  const uploadResponse = await res.json();
  const uploadUrl = uploadResponse.upload_url;

  const data = {
    audio_url: uploadUrl, // You can also use a URL to an audio or video file on the web
    speech_models: ["universal-3-pro", "universal-2"],
    language_detection: true,
    speech_threshold: 0.5,
  };

  const url = `${baseUrl}/v2/transcript`;
  res = await fetch(url, {
    method: "POST",
    headers: { ...headers, "Content-Type": "application/json" },
    body: JSON.stringify(data),
  });
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  const response = await res.json();

  const transcriptId = response.id;
  const pollingEndpoint = `${baseUrl}/v2/transcript/${transcriptId}`;

  while (true) {
    res = await fetch(pollingEndpoint, { headers });
    if (!res.ok) throw new Error(`Error: ${res.status}`);
    const transcriptionResult = await res.json();

    if (transcriptionResult.status === "completed") {
      console.log(transcriptionResult.text);
      break;
    } else if (transcriptionResult.status === "error") {
      throw new Error(`Transcription failed: ${transcriptionResult.error}`);
    } else {
      await new Promise((resolve) => setTimeout(resolve, 3000));
    }
  }
  ```
</CodeGroup>