> ## 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.

# Transcript export options

export const LanguageTable = ({languages, columns = 3}) => {
  return <div className="grid gap-2" style={{
    gridTemplateColumns: `repeat(${columns}, 1fr)`
  }}>
      {languages.map(language => <div key={language.code} className="flex justify-between items-center">
          <span>{language.name}</span>
          <code className="text-sm bg-gray-100 px-2 py-1 rounded">
            {language.code}
          </code>
        </div>)}
    </div>;
};

This page explains the different ways you can export and format your transcript data, including SRT/VTT caption files, paragraphs and sentences, and word-level timestamps.

The plain-text transcript returned in the `text` field is raw transcript text only — it does not include timestamps or speaker labels. To build a custom text export in a format such as `[Speaker] timecode -> text`, enable [speaker labels](/pre-recorded-audio/label-speakers) and construct the output from the `utterances` array (which contains `speaker`, `start`, `end`, and `text` for each utterance). See the [Timestamped transcripts](/guides/timestamped-transcripts) guide and the [Create subtitles with speaker labels](/pre-recorded-audio/guides/speaker_labelled_subtitles) cookbook for examples.

## Export SRT or VTT caption files

You can export completed transcripts in SRT or VTT format, which can be used for subtitles and closed captions in videos.

You can also customize the maximum number of characters per caption by specifying the `chars_per_caption` parameter.

<CodeGroup>
  ```python title="Python SDK" highlight={15-18}  expandable 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
  )

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

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

  srt = transcript.export_subtitles_srt(
    # Optional: Customize the maximum number of characters per caption
    chars_per_caption=32
    )

  with open(f"transcript_{transcript.id}.srt", "w") as srt_file:
    srt_file.write(srt)

  # vtt = transcript.export_subtitles_vtt()

  # with open(f"transcript_{transcript_id}.vtt", "w") as vtt_file:
  #   vtt_file.write(vtt)

  ```

  ```python title="Python" highlight={41}  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
  }

  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)

  # chars_per_caption is optional
  srt_response = requests.get(f"{polling_endpoint}/srt?chars_per_caption=32", headers=headers)

  with open(f"transcript_{transcript_id}.srt", "w") as srt_file:
    srt_file.write(srt_response.text)

  # vtt_response = requests.get(f"{polling_endpoint}/vtt", headers=headers)

  # with open(f"transcript_{transcript_id}.vtt", "w") as vtt_file:
  #   vtt_file.write(vtt_response.text)
  ```

  ```javascript title="JavaScript SDK" highlight={19}  expandable theme={null}
  import { AssemblyAI } from "assemblyai";
  import fs from "fs";

  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,
  };

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

    let srt = await client.transcripts.subtitles(transcript.id, "srt", 32);
    fs.writeFileSync(`transcript_${transcript.id}.srt`, srt);

    // let vtt = await client.transcripts.subtitles(transcript.id, 'vtt', 32)
    // fs.writeFileSync(`transcript_${transcript.id}.vtt`, vtt)
  };

  run();
  ```

  ```javascript title="JavaScript" highlight={44}  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,
  };

  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));
    }
  }

  const srtEndpoint = `${baseUrl}/v2/transcript/${transcriptId}/srt?chars_per_caption=32`;
  res = await fetch(srtEndpoint, { headers });
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  const srt = await res.text();

  fs.writeFileSync(`transcript_${transcriptId}.srt`, srt);

  // const vttEndpoint = `${baseUrl}/v2/transcript/${transcriptId}/vtt?chars_per_caption=32`
  // const vtt = await fetch(vttEndpoint, { headers }).then(res => res.text())

  // fs.writeFileSync(`transcript_${transcriptId}.vtt`, vtt)
  ```
</CodeGroup>

## Export paragraphs

You can retrieve transcripts that are automatically segmented into paragraphs. The text of the transcript is broken down by paragraphs, along with additional metadata.

<CodeGroup>
  ```python title="Python SDK" highlight={15-18}  expandable 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
  )

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

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

  paragraphs = transcript.get_paragraphs()
  for paragraph in paragraphs:
    print(paragraph.text)
    print()
  ```

  ```python title="Python" highlight={40-43}  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
  }

  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)

  paragraphs = requests.get(polling_endpoint + '/paragraphs', headers=headers).json()['paragraphs']
  for paragraph in paragraphs:
    print(paragraph['text'])
    print()
  ```

  ```javascript title="JavaScript SDK" highlight={16-19}  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,
  };

  const run = async () => {
    const transcript = await client.transcripts.transcribe(params);
    const { paragraphs } = await client.transcripts.paragraphs(transcript.id);
    for (const paragraph of paragraphs) {
      console.log(paragraph.text);
    }
  };

  run();
  ```

  ```javascript title="JavaScript" highlight={43-51}  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,
  };

  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));
    }
  }

  const paragraphsEndpoint = `${baseUrl}/v2/transcript/${transcriptId}/paragraphs`;

  res = await fetch(paragraphsEndpoint, { headers });
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  const paragraphsResponse = await res.json();
  const paragraphs = paragraphsResponse.paragraphs;

  for (const paragraph of paragraphs) {
    console.log(paragraph.text);
    console.log();
  }
  ```
</CodeGroup>

## Export sentences

You can retrieve transcripts that are automatically segmented into sentences, for a more reader-friendly experience. The text of the transcript is broken down by sentences, along with additional metadata.

<CodeGroup>
  ```python title="Python SDK" highlight={15-18}  expandable 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
  )

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

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

  sentences = transcript.get_sentences()
  for sentence in sentences:
    print(sentence.text)
    print()
  ```

  ```python title="Python" highlight={40-43}  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
  }

  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)

  sentences = requests.get(polling_endpoint + '/sentences', headers=headers).json()['sentences']
  for sentence in sentences:
    print(sentence['text'])
    print()
  ```

  ```javascript title="JavaScript SDK" highlight={16-20}  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,
  };

  const run = async () => {
    const transcript = await client.transcripts.transcribe(params);
    const { sentences } = await client.transcripts.sentences(transcript.id);
    for (const sentence of sentences) {
      console.log(sentence.text);
    }
  };

  run();
  ```

  ```javascript title="JavaScript" highlight={45-51}  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,
  };

  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));
    }
  }

  const sentencesEndpoint = `${baseUrl}/v2/transcript/${transcriptId}/sentences`;

  res = await fetch(sentencesEndpoint, { headers });
  if (!res.ok) throw new Error(`Error: ${res.status}`);
  const sentencesResponse = await res.json();
  const sentences = sentencesResponse.sentences;

  for (const sentence of sentences) {
    console.log(sentence.text);
    console.log();
  }
  ```
</CodeGroup>

The response is an array of objects, each representing a sentence or a paragraph in the transcript. See the [API reference](/api-reference/transcripts/get-sentences) for more info.

## Word-level timestamps

The response also includes an array with information about each word:

<CodeGroup>
  ```python title="Python SDK" highlight={13}  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
  )

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

  for word in transcript.words:
    print(f"Word: {word.text}, Start: {word.start}, End: {word.end}, Confidence: {word.confidence}")
  ```

  ```python title="Python" highlight={31-32}  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
  }

  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':
      for word in transcription_result['words']:
        print(f"Word: {word['text']}, Start: {word['start']}, End: {word['end']}, Confidence: {word['confidence']}")
      break

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

    else:
      time.sleep(3)

  ```

  ```javascript title="JavaScript SDK" highlight={22}  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,
  };

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

    console.log(transcript.text);

    // Print word-level details
    for (const word of transcript.words) {
      console.log(
        `Word: ${word.text}, Start: ${word.start}, End: ${word.end}, Confidence: ${word.confidence}`
      );
    }
  };

  run();
  ```

  ```javascript title="JavaScript" highlight={36-39}  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,
  };

  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);
      // Print word-level details
      for (const word of transcriptionResult.words) {
        console.log(
          `Word: ${word.text}, Start: ${word.start}, End: ${word.end}, Confidence: ${word.confidence}`
        );
      }
      break;
    } else if (transcriptionResult.status === "error") {
      throw new Error(`Transcription failed: ${transcriptionResult.error}`);
    } else {
      await new Promise((resolve) => setTimeout(resolve, 3000));
    }
  }
  ```
</CodeGroup>

### API Reference

```js expandable theme={null}
{
    words: [
      {
        text: "Smoke",
        start: 240,
        end: 640,
        confidence: 0.70473,
        speaker: null,
      },
      {
        text: "from",
        start: 680,
        end: 968,
        confidence: 0.99967,
        speaker: null,
      },
      {
        text: "hundreds",
        start: 1024,
        end: 1416,
        confidence: 0.99795,
        speaker: null,
      },
      {
        text: "of",
        start: 1448,
        end: 1592,
        confidence: 0.99926,
        speaker: null,
      },
      {
        text: "wildfires",
        start: 1616,
        end: 2248,
        confidence: 0.99838,
        speaker: null,
      },
      {
        text: "in",
        start: 2264,
        end: 2440,
        confidence: 0.99782,
        speaker: null,
      },
      {
        text: "Canada",
        start: 2480,
        end: 2968,
        confidence: 0.99977,
        speaker: null,
      },
    ],
  
}
```

## Additional resources

<CardGroup cols={2}>
  <Card title="Is there a way to generate SRT or VTT captions with speaker labels?" icon="circle-question" iconType="regular" href="/faq/is-there-a-way-to-generate-srt-or-vtt-captions-with-speaker-labels">
    Learn how to create caption files that include speaker identification.
  </Card>
</CardGroup>