48 lines
2.9 KiB
Markdown
48 lines
2.9 KiB
Markdown
# WhisperBenchmarks
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This repository provides easy-to-use benchmarks using audio and video content from the Internet Archive, specifically targeting various challenging scenarios in audio recordings.
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Based on https://gitlab.com/aadnk/whisper-webui
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## Models
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| Model | Command |
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|faster-large-v3| --whisper_implementation faster-whisper --model large-v3 |
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|faster-medium| --whisper_implementation faster-whisper --model medium |
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|faster-small| --whisper_implementation faster-whisper --model small |
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|faster-tiny| --whisper_implementation faster-whisper --model tiny |
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## Videos
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Videos are chosen for being short and matching their given category
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| Categories | Title | Links | Length | Type |
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| Poor mic placement | Body camera footage from July 10 traffic stop | [Internet Archive](https://archive.org/details/cobmn-Body_camera_footage_from_July_10_traffic_stop) | 2:22 | MP4 |
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| Thick accents | Moonshine for Medicine Popcorn Sutton | [Internet Archive](https://archive.org/details/this-is-the-last-dam-run-of-likker-ill-ever-make-full-movie/+Moonshine+for+Medicine++++Popcorn+Sutton.mp4) | 1:35 | MP4 |
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| Artifacts in audio | 2002 007 Movie Trailer Commercial Bad Video | [Internet Archive](https://archive.org/details/2002variouscommercials/2002+007+Movie+Trailer+Commercial+Bad+Video.mp4) | 0:14 | MP4 |
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| Ideal audio (one speaker) | 8 Bit Bookclub | [Internet Archive](https://archive.org/details/8-bit-bookclub/36+-+ANNOUNCEMENT++SUMMER+HIATUS.mp3) | 1:44 | MP3 |
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## How to Run Whisper Benchmarks
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-- TODO --
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## Results
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Results are for the complete run which includes loading the model, running VAD, and running the transcription. Links are embeded in the results for each category
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### CPU Benchmarks
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| CPU Model | Poor mic placement (m:s:ms) | Thick accents (m:s:ms) | Artifacts in audio (m:s:ms) | Ideal audio (m:s:ms) | (Docker/Native) | Model |
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### GPU Benchmarks
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| GPU Model | Poor mic placement (m:s:ms) | Thick accents (m:s:ms) | Artifacts in audio (m:s:ms) | Ideal audio (m:s:ms) | (Docker/Native) | Model |
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| RTX 2060S | [00:02.14](https://git.myco.systems/brooke/whisperbenchmarks/src/branch/main/benchmark-outputs/Body_camera_footage_from_July_10_traffic_stop.mp4-subs.srt) | [00:09.99](https://git.myco.systems/brooke/whisperbenchmarks/src/branch/main/benchmark-outputs/Moonshine%20for%20Medicine%20Popcorn%20Sutton.mp4-subs.srt) | [00:05.07](https://git.myco.systems/brooke/whisperbenchmarks/src/branch/main/benchmark-outputs/2002%20007%20Movie%20Trailer%20Commercial%20Bad%20Video.mp4-subs.srt) | [00:11.02](https://git.myco.systems/brooke/whisperbenchmarks/src/branch/main/benchmark-outputs/36%20-%20ANNOUNCEMENT%20SUMMER%20HIATUS.mp3-subs.srt) | Native | Faster-Medium |
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## Todo:
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- [ ] Write easy bash scripts for running a set of benchmarks with an easy cleanup
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- [ ] Finalize a standard format for exporting the data into a spreadsheet
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