Whisper openai low processing speed with large files

Whisper openai low processing speed with large files - Stack Overflow

Use the openai Whisper API. They've optimised the speed to achieve a real time factor of ~0.1 (meaning 180sec audio will take 18sec to process).

Very slow transcribing on CPU #369 - openai whisper - GitHub

I have a server with Ryzen 5 3600, and transcribing times are abysmally long. I am using Polish language, with medium model, and for file with 31s duration it ...

Whisper API seems very slow or doesn't always work - Community

GitHub - openai/whisper: Robust Speech Recognition via Large-Scale Weak... ... I use this API for an audio file hosting site, so I can't ask each ...

OpenAI Whisper hangs/freezes on some audio files - Stack Overflow

I am experiencing issues with OpenAI's whisper and faster-whisper when processing audio files. Specifically, some of the files fail to fully process and the ...

How to use whisper to handle long video? - OpenAI Developer Forum

... processor ASICs and transcribe 50x faster than OpenAI can. https ... Whisper JAX ⚡ can now be used as an endpoint - send audio files ...

Open AI's new Whisper Turbo model runs 5.4 times faster LOCALLY ...

Basically, it performs very similar to large-v2/v3 in terms of WER (only slight degradation) and is around 130x real-time speed (with batch size ...

Optimise OpenAI Whisper API: Audio Format, Sampling Rate and ...

... slow... Tagged with openai, whisper, programming, audio ... large audio files. However, tinkering with the format of the ...

OpenAI's Whisper: Reading the Fine Print - Deepgram Blog ⚡

Larger models tend to provide higher accuracy at the tradeoff of increased processing time and compute cost; to increase the processing speed ...

Making OpenAI Whisper faster - Nikolas' Blog

Faster-whisper can transcribe the same audio file in 2 minutes and 44 seconds. The numbers from above were provided by the author of the package ...

Whisper Lesson 4 – Speeding Up or Outsourcing the Processing

It uses CTranslate2, a fast engine for Transformer models, and is up to 4 times faster and uses considerably less memory than the original openai/whisper while ...

openai/whisper: Robust Speech Recognition via Large ... - GitHub

Internally, the transcribe() method reads the entire file and processes the audio with a sliding 30-second window, performing autoregressive sequence-to- ...

Whisper API Limits - Transcriptions - OpenAI Developer Forum

I'm testing the whisper api to transcribe audio. In the documentation it says that the file size limit is 25MB but if I try to send files ...

Speech-to-Text | Quickly get a transcription of a large audio file in ...

faster-whisper is a reimplementation of OpenAI's Whisper model using CTranslate2, which is a fast inference engine for Transformer models. This ...

Whisper API, increase file limit >25 MB - OpenAI Developer Forum

The Whisper API only supports files that are less than 25 MB. If you have an audio file that is longer than that, you will need to break it up into chunks of ...

How to chunk down audio to 25mb max size for openai whisper ...

Seeking Solution: Splitting Large Podcast Files for OpenAI Processing ... You can use file compression to lower the size of your file. I ...

Whisper API quality degrading over time - OpenAI Developer Forum

... processing 30 second files with about 23-30 words in total. I've put in a conditional failsafe flow based on word count, but my 20% success rate ...

Make OpenAI Whisper 2-4x Faster in Python in 100 Seconds

allows the OpenAI whisper models to run on CTranslate2 instead of Pytorch. This results in 2-4x speed increases to transcribe audio to text ...

Openai whisper api is too slow (23 minute), unable to use

Openai whisper api is too slow (23 minute), unable to use ... My test case is put a 20 minute cantonese audio file to test the processing speed of ...

openai/whisper-large-v3-turbo - Hugging Face

You can apply additional speed and memory improvements to Whisper to further reduce the inference speed and VRAM requirements. ... Chunked: splits long audio ...

Whisper API cut output short when input is large (smaller than 25 MB)

If the input is large (approximately larger than 10MB), the output will be cut short. The larger the input is, the shorter the output is.