sidedwards/whisperx – Run with an API on Replicate

sidedwards / whisperx

WhisperX with accelerated transcription and advanced speaker diarization provides fast and accurate transcriptions with speaker segments.

Cold

Public
190 runs
L40S
GitHub

Run with an API

Playground API Examples README Versions

Input

audio_file

file

Audio file (mp3 or mp4)

audio_blob

file

Audio file as a Blob (mp3 or mp4)

language

string

Shift + Return to add a new line

ISO code of the language spoken in the audio, specify None to perform language detection

language_detection_min_prob

number

If language is not specified, then the language will be detected recursively on different parts of the file until it reaches the given probability

Default: 0

language_detection_max_tries

integer

If language is not specified, then the language will be detected following the logic of language_detection_min_prob parameter, but will stop after the given max retries. If max retries is reached, the most probable language is kept.

Default: 5

initial_prompt

string

Shift + Return to add a new line

Optional text to provide as a prompt for the first window

batch_size

integer

Parallelization of input audio transcription

Default: 64

temperature

number

Temperature to use for sampling

Default: 0

vad_onset

number

VAD onset

Default: 0.5

vad_offset

number

VAD offset

Default: 0.363

align_output

boolean

Aligns whisper output to get accurate word-level timestamps

Default: false

diarization

boolean

Assign speaker ID labels

Default: false

huggingface_access_token

string

Shift + Return to add a new line

To enable diarization, please enter your HuggingFace token (read). You need to accept the user agreement for the models specified in the README.

min_speakers

integer

Minimum number of speakers if diarization is activated (leave blank if unknown)

max_speakers

integer

Maximum number of speakers if diarization is activated (leave blank if unknown)

debug

boolean

Print out compute/inference times and memory usage information

Default: false

Run this model in Node.js with one line of code:

npx create-replicate --model=sidedwards/whisperx

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run sidedwards/whisperx using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "sidedwards/whisperx:e9625c116484a995c0f8c77f1744ea8c518ff68528f254721caa525a69ab3236",
  {
    input: {
      debug: false,
      vad_onset: 0.5,
      batch_size: 64,
      vad_offset: 0.363,
      diarization: false,
      temperature: 0,
      align_output: false,
      language_detection_min_prob: 0,
      language_detection_max_tries: 5
    }
  }
);
console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run sidedwards/whisperx using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "sidedwards/whisperx:e9625c116484a995c0f8c77f1744ea8c518ff68528f254721caa525a69ab3236",
    input={
        "debug": False,
        "vad_onset": 0.5,
        "batch_size": 64,
        "vad_offset": 0.363,
        "diarization": False,
        "temperature": 0,
        "align_output": False,
        "language_detection_min_prob": 0,
        "language_detection_max_tries": 5
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run sidedwards/whisperx using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "e9625c116484a995c0f8c77f1744ea8c518ff68528f254721caa525a69ab3236",
    "input": {
      "debug": false,
      "vad_onset": 0.5,
      "batch_size": 64,
      "vad_offset": 0.363,
      "diarization": false,
      "temperature": 0,
      "align_output": false,
      "language_detection_min_prob": 0,
      "language_detection_max_tries": 5
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.

Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

WhisperX with accelerated transcription and advanced speaker diarization provides fast and accurate transcriptions with speaker segments.

Based on: https://github.com/victor-upmeet/whisperx-replicate

Citation

@misc{bain2023whisperx,
      title={WhisperX: Time-Accurate Speech Transcription of Long-Form Audio}, 
      author={Max Bain and Jaesung Huh and Tengda Han and Andrew Zisserman},
      year={2023},
      eprint={2303.00747},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}

For more information, visit the WhisperX GitHub repository.