# WhisperBenchmarks

This repo has been alterted to aid in my process of understanding the process of benchmarking WhisperX, after I take the time to do a bit more research I can start refocusing the idea to a simple script.

## Videos

Videos are chosen for being short and matching their given category

| Categories | Title | Link | Length | Instant Download |
|-|-|-|-|-|
| 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](https://archive.org/download/cobmn-Body_camera_footage_from_July_10_traffic_stop/Body_camera_footage_from_July_10_traffic_stop.mp4) |
| 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](https://archive.org/download/this-is-the-last-dam-run-of-likker-ill-ever-make-full-movie/%20Moonshine%20for%20Medicine%20%20%20%20Popcorn%20Sutton.mp4) |
| 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](https://archive.org/download/2002variouscommercials/2002%20A%20Touch%20Of%20Class%20Limos%20Bridal%20Show%20Wilton%20Mall%20Saratoga%20Commercial.mp4) |
| Ideal audio (one speaker) | 8 Bit Bookclub | [Internet Archive](https://archive.org/details/8-bit-bookclub/36+-+ANNOUNCEMENT++SUMMER+HIATUS.mp3) | 1:44 | [MP3](https://archive.org/download/8-bit-bookclub/36%20-%20ANNOUNCEMENT%20%20SUMMER%20HIATUS.mp3) |
| Long form (many speakers) | Bionic Woman "Black Magic" (1976) | [Internet Archive](https://archive.org/details/bionic-woman-black-magic) | 43:53 | [MP4](https://archive.org/download/bionic-woman-black-magic/Black%20Magic-NA_x264.mp4) |

## How to Run Whisper Benchmarks

Two tools are recommended, [Hyperfine](https://github.com/sharkdp/hyperfine) is a shell benchmarking tool written in rust, and [WhisperX](https://github.com/m-bain/whisperX) a re-implementation of whisper that boasts a 70x increase in performance.

To use WhisperX I would recommend having a HuggingFace account and agreeing to these two repos (https://huggingface.co/pyannote/speaker-diarization-3.1/tree/main) (https://huggingface.co/pyannote/segmentation-3.0).
Then, you'll have to include your HF token in every WhisperX command.

## Results

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

### CPU Benchmarks

|  CPU Model | Poor mic placement (m:s:ms) | Thick accents (m:s:ms) | Artifacts in audio (m:s:ms) | Ideal audio (m:s:ms) | Long form | (Docker/Native) | Model |
|-|-|-|-|-|-|-|-|

### GPU Benchmarks

|  GPU Model | Poor mic placement (m:s:ms) | Thick accents (m:s:ms) | Artifacts in audio (m:s:ms) | Ideal audio (m:s:ms) | Long form (m:s:ms) | (Docker/Native) | Model |
|-|-|-|-|-|-|-|-|

## Todo: