├── .env
├── img
    └── screenshort.png
├── Pipfile
├── Dockerfile
├── app.py
├── requirements.txt
├── README.md
└── Pipfile.lock


/.env:
--------------------------------------------------------------------------------
1 | GRADIO_SERVER_PORT=8000


--------------------------------------------------------------------------------
/img/screenshort.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/innovatorved/whisper-openai-gradio-implementation/HEAD/img/screenshort.png


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/Pipfile:
--------------------------------------------------------------------------------
1 | [packages]
2 | whisper = {git = "https://github.com/openai/whisper.git"}
3 | gradio = "*"
4 | ffmpeg-python = "*"
5 | 


--------------------------------------------------------------------------------
/Dockerfile:
--------------------------------------------------------------------------------
 1 | FROM python:3.8-slim-buster
 2 | 
 3 | RUN apt update && apt install -y ffmpeg git
 4 | 
 5 | WORKDIR /app
 6 | 
 7 | COPY requirements.txt requirements.txt
 8 | RUN pip3 install -r requirements.txt
 9 | 
10 | EXPOSE 8000 8000
11 | 
12 | ENV GRADIO_SERVER_PORT 8000
13 | 
14 | COPY . .
15 | 
16 | CMD [ "python3", "app.py"]
17 | 


--------------------------------------------------------------------------------
/app.py:
--------------------------------------------------------------------------------
 1 | import whisper
 2 | 
 3 | # You can choose your model from - see it on readme file and update the modelname
 4 | modelname = "base"
 5 | model = whisper.load_model(modelname)
 6 | 
 7 | import gradio as gr 
 8 | import time
 9 | 
10 | def SpeechToText(audio):
11 |     if audio == None : return "" 
12 |     time.sleep(1)
13 | 
14 |     audio = whisper.load_audio(audio)
15 |     audio = whisper.pad_or_trim(audio)
16 | 
17 |     # make log-Mel spectrogram and move to the same device as the model
18 |     mel = whisper.log_mel_spectrogram(audio).to(model.device)
19 | 
20 |     # Detect the Max probability of language ?
21 |     _, probs = model.detect_language(mel)
22 |     language = max(probs, key=probs.get)
23 | 
24 |     #  Decode audio to Text
25 |     options = whisper.DecodingOptions(fp16 = False)
26 |     result = whisper.decode(model, mel, options)
27 |     return (language , result.text)
28 | 
29 | print("Starting the Gradio Web UI")
30 | gr.Interface(
31 |     title = 'OpenAI Whisper implementation on Gradio Web UI', 
32 |     fn=SpeechToText, 
33 |     
34 |     inputs=[
35 |         gr.Audio(source="microphone", type="filepath")
36 |     ],
37 |     outputs=[
38 |         "label",
39 |         "textbox",
40 |     ],
41 |     live=True
42 | ).launch(
43 |     debug=False,
44 | )


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
 1 | aiofiles==23.1.0
 2 | aiohttp==3.8.4
 3 | aiosignal==1.3.1
 4 | altair==5.0.1
 5 | anyio==3.7.0
 6 | async-timeout==4.0.2
 7 | attrs==23.1.0
 8 | bcrypt==4.0.0
 9 | certifi==2023.5.7
10 | cffi==1.15.1
11 | charset-normalizer==3.1.0
12 | click==8.1.3
13 | contourpy==1.0.7
14 | cryptography==38.0.1
15 | cycler==0.11.0
16 | exceptiongroup==1.1.1
17 | fastapi==0.95.2
18 | ffmpeg-python==0.2.0
19 | ffmpy==0.3.0
20 | filelock==3.12.0
21 | fonttools==4.39.4
22 | frozenlist==1.3.3
23 | fsspec==2023.5.0
24 | future==0.18.2
25 | gradio==3.32.0
26 | gradio_client==0.2.5
27 | h11==0.14.0
28 | httpcore==0.17.2
29 | httpx==0.24.1
30 | huggingface-hub==0.14.1
31 | idna==3.4
32 | Jinja2==3.1.2
33 | jsonschema==4.17.3
34 | kiwisolver==1.4.4
35 | linkify-it-py==2.0.2
36 | markdown-it-py==2.2.0
37 | MarkupSafe==2.1.2
38 | matplotlib==3.7.1
39 | mdit-py-plugins==0.3.3
40 | mdurl==0.1.2
41 | more-itertools==8.14.0
42 | multidict==6.0.4
43 | numpy==1.24.3
44 | orjson==3.8.14
45 | packaging==23.1
46 | pandas==2.0.1
47 | paramiko==2.11.0
48 | Pillow==9.5.0
49 | pycparser==2.21
50 | pycryptodome==3.15.0
51 | pydantic==1.10.8
52 | pydub==0.25.1
53 | Pygments==2.15.1
54 | PyNaCl==1.5.0
55 | pyparsing==3.0.9
56 | pyrsistent==0.19.3
57 | python-dateutil==2.8.2
58 | python-multipart==0.0.6
59 | pytz==2023.3
60 | PyYAML==6.0
61 | regex==2022.9.13
62 | requests==2.31.0
63 | rfc3986==1.5.0
64 | semantic-version==2.10.0
65 | six==1.16.0
66 | sniffio==1.3.0
67 | starlette==0.27.0
68 | tokenizers==0.12.1
69 | toolz==0.12.0
70 | torch==1.12.1
71 | tqdm==4.65.0
72 | transformers==4.22.2
73 | typing_extensions==4.6.2
74 | tzdata==2023.3
75 | uc-micro-py==1.0.2
76 | urllib3==2.0.2
77 | uvicorn==0.22.0
78 | websockets==11.0.3
79 | whisper @ git+https://github.com/openai/whisper.git@0b1ba3d46ebf7fe6f953acfd8cad62a4f851b49f
80 | yarl==1.9.2
81 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | 
 2 | # Whisper OpenAi Tool Gradio Web implementation
 3 | Whisper is an automatic speech recognition (ASR) system Gradio Web UI Implementation
 4 | 
 5 | 
 6 | 
 7 | ## Installation
 8 | 
 9 | Install ffmeg on Your Device
10 | 
11 | ```bash
12 |   # on Ubuntu or Debian
13 |   sudo apt update
14 |   sudo apt install ffmpeg
15 | 
16 |   # on MacOS using Homebrew (https://brew.sh/)
17 |   brew install ffmpeg
18 | 
19 |   # on Windows using Chocolatey (https://chocolatey.org/)
20 |   choco install ffmpeg
21 | 
22 |   # on Windows using Scoop (https://scoop.sh/)
23 |   scoop install ffmpeg
24 | ```
25 | 
26 | Download Program
27 | 
28 | ```bash
29 |   mkdir whisper-sppech2txt
30 |   cd whisper-sppech2txt
31 |   git clone https://github.com/innovatorved/whisper-openai-gradio-implementation.git .
32 |   pip install -r requirements.txt
33 | ```
34 |     
35 | 
36 | Run Program
37 | 
38 | ```bash
39 |   python app.py
40 | 
41 | ```
42 | 
43 | ## Available models and languages ([Credit](https://github.com/innovatorved/whisper-openai-gradio-implementation/blob/main/README.md))
44 | 
45 | There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed. 
46 | 
47 | 
48 | |  Size  | Parameters | English-only model | Multilingual model | Required VRAM | Relative speed |
49 | |:------:|:----------:|:------------------:|:------------------:|:-------------:|:--------------:|
50 | |  tiny  |    39 M    |     `tiny.en`      |       `tiny`       |     ~1 GB     |      ~32x      |
51 | |  base  |    74 M    |     `base.en`      |       `base`       |     ~1 GB     |      ~16x      |
52 | | small  |   244 M    |     `small.en`     |      `small`       |     ~2 GB     |      ~6x       |
53 | | medium |   769 M    |    `medium.en`     |      `medium`      |     ~5 GB     |      ~2x       |
54 | | large  |   1550 M   |        N/A         |      `large`       |    ~10 GB     |       1x       |
55 | 
56 | For English-only applications, the `.en` models tend to perform better, especially for the `tiny.en` and `base.en` models. We observed that the difference becomes less significant for the `small.en` and `medium.en` models.
57 | 
58 | 
59 | ## Screenshots
60 | 
61 | ![Screenshort](https://raw.githubusercontent.com/innovatorved/whisper-openai-gradio-implementation/main/img/screenshort.png)
62 | ## License
63 | 
64 | [MIT](https://choosealicense.com/licenses/mit/)
65 | 
66 | 
67 | ## Reference
68 | 
69 | - [https://github.com/openai/whisper](https://github.com/openai/whisper)
70 | - [https://openai.com/blog/whisper/](https://openai.com/blog/whisper/)
71 | 
72 |   
73 | ## Authors
74 | 
75 | - [Ved Gupta](https://www.github.com/innovatorved)
76 | 
77 |   
78 | ## 🚀 About Me
79 | I'm a Developer i will feel the code then write .
80 | 
81 |   
82 | ## Support
83 | 
84 | For support, email vedgupta@protonmail.com


--------------------------------------------------------------------------------
/Pipfile.lock:
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1788 |                 "sha256:a74dcbfe780e62f4b5a062714576f16c2f3493a0394e555ab141bf0d746bb955",
1789 |                 "sha256:a83503934c6273806aed765035716216cc9ab4e0364f7f066227e1aaea90b8d0",
1790 |                 "sha256:ac9bb4c5ce3975aeac288cfcb5061ce60e0d14d92209e780c93954076c7c4367",
1791 |                 "sha256:aff634b15beff8902d1f918012fc2a42e0dbae6f469fce134c8a0dc51ca423bb",
1792 |                 "sha256:b03917871bf859a81ccb180c9a2e6c1e04d2f6a51d953e6a5cdd70c93d4e5a2a",
1793 |                 "sha256:b124e2a6d223b65ba8768d5706d103280914d61f5cae3afbc50fc3dfcc016623",
1794 |                 "sha256:b25322201585c69abc7b0e89e72790469f7dad90d26754717f3310bfe30331c2",
1795 |                 "sha256:b7232f8dfbd225d57340e441d8caf8652a6acd06b389ea2d3222b8bc89cbfca6",
1796 |                 "sha256:b8cc1863402472f16c600e3e93d542b7e7542a540f95c30afd472e8e549fc3f7",
1797 |                 "sha256:b9a4e67ad7b646cd6f0938c7ebfd60e481b7410f574c560e455e938d2da8e0f4",
1798 |                 "sha256:be6b3fdec5c62f2a67cb3f8c6dbf56bbf3f61c0f046f84645cd1ca73532ea051",
1799 |                 "sha256:bf74d08542c3a9ea97bb8f343d4fcbd4d8f91bba5ec9d5d7f792dbe727f88938",
1800 |                 "sha256:c027a6e96ef77d401d8d5a5c8d6bc478e8042f1e448272e8d9752cb0aff8b5c8",
1801 |                 "sha256:c0c77533b5ed4bcc38e943178ccae29b9bcf48ffd1063f5821192f23a1bd27b9",
1802 |                 "sha256:c1012fa63eb6c032f3ce5d2171c267992ae0c00b9e164efe4d73db818465fac3",
1803 |                 "sha256:c3a53ba34a636a256d767c086ceb111358876e1fb6b50dfc4d3f4951d40133d5",
1804 |                 "sha256:d4e2c6d555e77b37288eaf45b8f60f0737c9efa3452c6c44626a5455aeb250b9",
1805 |                 "sha256:de119f56f3c5f0e2fb4dee508531a32b069a5f2c6e827b272d1e0ff5ac040333",
1806 |                 "sha256:e65610c5792870d45d7b68c677681376fcf9cc1c289f23e8e8b39c1485384185",
1807 |                 "sha256:e9fdc7ac0d42bc3ea78818557fab03af6181e076a2944f43c38684b4b6bed8e3",
1808 |                 "sha256:ee4afac41415d52d53a9833ebae7e32b344be72835bbb589018c9e938045a560",
1809 |                 "sha256:f364d3480bffd3aa566e886587eaca7c8c04d74f6e8933f3f2c996b7f09bee1b",
1810 |                 "sha256:f3b078dbe227f79be488ffcfc7a9edb3409d018e0952cf13f15fd6512847f3f7",
1811 |                 "sha256:f4e2d08f07a3d7d3e12549052eb5ad3eab1c349c53ac51c209a0e5991bbada78",
1812 |                 "sha256:f7a3d8146575e08c29ed1cd287068e6d02f1c7bdff8970db96683b9591b86ee7"
1813 |             ],
1814 |             "markers": "python_version >= '3.7'",
1815 |             "version": "==1.9.2"
1816 |         }
1817 |     },
1818 |     "develop": {}
1819 | }
1820 | 


--------------------------------------------------------------------------------