whisper.cpp/examples/main
bobqianic 7e54df414e
whisper : significantly improve the inference quality (#1148)
* Fix MSVC compile error C3688

Instead of simply using 'add_compile_options(/utf-8)' to address the MSVC compile error C3688, a better approach would be to handle it in a way that prevents passing '/utf-8' to NVCC.

* Significantly improve inference quality

In the function `log_mel_spectrogram_worker_thread`, there's an array out-of-bounds issue occurring during the calculation of complex number moduli. This issue is causing disruptions in the FFT spectrum, which, in turn, is reducing the quality of inference.

* Significantly improve inference quality

At last, I've pinpointed the actual source of the problem. Given that the frequency spectrum generated from real input data is symmetrical around the Nyquist frequency, there's a for-loop within the `log_mel_spectrogram_worker_thread` function that attempts to fold the frequency spectrum. Regrettably, a bug within this for-loop is causing a frame shift in the frequency spectrum. The previous attempt to remedy this, which involved using `fft_size + 1` when calculating the modulus, was merely a band-aid solution and did not address the underlying issue.

* Addressed a few minor issues

Fixed the issue of `fft_out` continuously expanding. Resolved the fallback caused by using 'break' instead of `fft_in[j] = 0`.

* Significantly improve inference quality 

Thanks for your patience everyone. It's finally sorted out. Now, the right side of the FFT spectrum is being flipped over to the left, and the amplitudes at corresponding positions on the left and right are added together (the spectrum on the left needs to be shifted by one position), then the average is calculated. FFT_OUT[0] is no longer discarded, making full use of the limited space to pack in more information.

* Add annotation and performance improvement

* Calculate FFT only when fft_in are not all zero

* Some minor performance improvement

* Fixed a bug impacting inference quality

* The first version after all the analysis is completed.

* Fix some bugs and add debug mode

* Fixed several bugs

* Temporarily disable speed-up mode and add debug mode.

* Add debug mode

* Disable speed-up mode and add debug mode

* Fix CI error (#1)

* Fix error

* Fix error

* Fixed several bugs including [BLANK_AUDIO] problem

* Remove Hard-coded hann window

* Some Final Fix (#2)

* Fix error

* Fix error

* Probably the last commit

* Probably the last commit

* whisper : minor coding style changes

* whisper : remove debug from public API

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-08-27 19:51:33 +03:00
..
CMakeLists.txt examples : refactor in order to reuse code and reduce duplication (#482) 2023-02-15 19:28:10 +02:00
main.cpp whisper : significantly improve the inference quality (#1148) 2023-08-27 19:51:33 +03:00
README.md main : provide option for creating JSON output (#615) 2023-03-22 21:37:36 +02:00

main

This is the main example demonstrating most of the functionality of the Whisper model. It can be used as a reference for using the whisper.cpp library in other projects.

./main -h

usage: ./main [options] file0.wav file1.wav ...

options:
  -h,        --help              [default] show this help message and exit
  -t N,      --threads N         [4      ] number of threads to use during computation
  -p N,      --processors N      [1      ] number of processors to use during computation
  -ot N,     --offset-t N        [0      ] time offset in milliseconds
  -on N,     --offset-n N        [0      ] segment index offset
  -d  N,     --duration N        [0      ] duration of audio to process in milliseconds
  -mc N,     --max-context N     [-1     ] maximum number of text context tokens to store
  -ml N,     --max-len N         [0      ] maximum segment length in characters
  -bo N,     --best-of N         [5      ] number of best candidates to keep
  -bs N,     --beam-size N       [-1     ] beam size for beam search
  -wt N,     --word-thold N      [0.01   ] word timestamp probability threshold
  -et N,     --entropy-thold N   [2.40   ] entropy threshold for decoder fail
  -lpt N,    --logprob-thold N   [-1.00  ] log probability threshold for decoder fail
  -su,       --speed-up          [false  ] speed up audio by x2 (reduced accuracy)
  -tr,       --translate         [false  ] translate from source language to english
  -di,       --diarize           [false  ] stereo audio diarization
  -nf,       --no-fallback       [false  ] do not use temperature fallback while decoding
  -otxt,     --output-txt        [false  ] output result in a text file
  -ovtt,     --output-vtt        [false  ] output result in a vtt file
  -osrt,     --output-srt        [false  ] output result in a srt file
  -owts,     --output-words      [false  ] output script for generating karaoke video
  -ocsv,     --output-csv        [false  ] output result in a CSV file
  -oj,       --output-json       [false  ] output result in a JSON file
  -of FNAME, --output-file FNAME [       ] output file path (without file extension)
  -ps,       --print-special     [false  ] print special tokens
  -pc,       --print-colors      [false  ] print colors
  -pp,       --print-progress    [false  ] print progress
  -nt,       --no-timestamps     [true   ] do not print timestamps
  -l LANG,   --language LANG     [en     ] spoken language ('auto' for auto-detect)
             --prompt PROMPT     [       ] initial prompt
  -m FNAME,  --model FNAME       [models/ggml-base.en.bin] model path
  -f FNAME,  --file FNAME        [       ] input WAV file path