SUPER Fast AI Real Time Speech to Text Transcribtion - Faster Whisper / Python
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- čas přidán 25. 06. 2024
- SUPER Fast AI Real Time Voice to Text Transcribtion - Faster Whisper / Python
👊 Become a member and get access to GitHub:
/ allaboutai
Get a FREE 45+ ChatGPT Prompts PDF here:
📧 Join the newsletter:
www.allabtai.com/newsletter/
🌐 My website:
www.allabtai.com
Faster-Whisperer:
github.com/SYSTRAN/faster-whi...
I created a almost zero latency real time AI voice to text transcribtion using faster whisperer and python. We are gonna look at some use cases for the script and a preview of my upcoming video. Enjoy!
00:00 Intro
00:21 Real Time AI Transcribtion "Mr.Beast"
01:25 Setup / Python Code
03:33 Real Time AI Transcribtion "Sentiment Analysis"
05:51 Real Time AI Transcribtion "Secret Project"
08:14 Conclusion - Věda a technologie
Epic! - These videos are some of the best stuff on CZcams - love the idea with the image generation at the end
This is amazing and inspiring. I love the ending of the video and can’t wait for Wednesday. As a dyslexic person I think you unlocked a new use case for learning.
wow !! great video !!! Thank you for being so generous and teaching this to us, this is epic stuff! I can already start see all kinds of use cases, I cant wait to get it running, I'm really looking forward to Wednesday's video . Thanks again from Canada
Excellent! Thank you so much for sharing!
Awesome bro! ❤
Good to see transcription and generate responses as audio in real-time for phone call
Fantastic !!! A bit fast in explaining and showing, but I can always pause!
There is a product for Live video Transcription there. Live text services are expensive and does not work on many current languages.. Set up a server/service that will ingest a RTMP video source, delay the video and overlay text on video in perfect sync. then offer RTMP output with burned in Live text. :) There is need for this service.
Gerçekten çok iyisiniz.
Amazing and inspiring work! Kris what about something less powerful but better accessible in terms of hardware?
Thanks for sharing your knowledge/experience.
I'm bit perplexed. The description here mentions 45+ prompts in the PDF book, the newsletter website says 40+, and the PDF doc says 35+. Which number is correct?
Code:
import os
import time
import wave
import pyaudio
from faster_whisper import WhisperModel
# Определяем константы
NEON_GREEN = '\033[32m'
RESET_COLOR = '\033[0m'
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
# Функция для записи аудио-фрагмента
def record_chunk(p, stream, file_path, chunk_length=1):
"""
Записывает аудиофрагмент в файл.
Args:
p (pyaudio.PyAudio): Объект PyAudio.
stream (pyaudio.Stream): Поток PyAudio.
file_path (str): Путь к файлу, куда будет записан аудиофрагмент.
chunk_length (int): Длина аудиофрагмента в секундах.
Returns:
None
"""
frames = []
for _ in range(0, int(16000 / 1024 * chunk_length)):
data = stream.read(1024)
frames.append(data)
wf = wave.open(file_path, 'wb')
wf.setnchannels(1)
wf.setsampwidth(p.get_sample_size(pyaudio.paInt16))
wf.setframerate(16000)
wf.writeframes(b''.join(frames))
wf.close()
def transcribe_chunk(model, file_path):
segments, info = model.transcribe(file_path, beam_size=7)
transcription = ''.join(segment.text for segment in segments)
return transcription
def main2():
"""
Основная функция программы.
"""
# Выбираем модель Whisper
model = WhisperModel("medium", device="cuda", compute_type="float16")
# Инициализируем PyAudio
p = pyaudio.PyAudio()
# Открываем поток записи
stream = p.open(format=pyaudio.paInt16, channels=1, rate=16000, input=True, frames_per_buffer=1024)
# Инициализируем пустую строку для накопления транскрипций
accumulated_transcription = ""
try:
while True:
# Записываем аудиофрагмент
chunk_file = "temp_chunk.wav"
record_chunk(p, stream, chunk_file)
# Транскрибируем аудиофрагмент
transcription = transcribe_chunk(model, chunk_file)
print(NEON_GREEN + transcription + RESET_COLOR)
# Удаляем временный файл
os.remove(chunk_file)
# Добавляем новую транскрипцию к накопленной транскрипции
accumulated_transcription += transcription + " "
except KeyboardInterrupt:
print("Stopping...")
# Записываем накопленную транскрипцию в лог-файл
with open("log.txt", "w") as log_file:
log_file.write(accumulated_transcription)
finally:
print("LOG" + accumulated_transcription)
# Закрываем поток записи
stream.stop_stream()
stream.close()
# Останавливаем PyAudio
p.terminate()
if __name__ == "__main__":
main2()
I LOVE U
@@josequinonez2941 can u share me the code in engish?
Tips: You can transform your device's audio output into a "microphone" on Windows, so you don't need to place your headphones over your microphone.
1. Press Windows key + R -> type "mmsys.cpl"
2. In the Recording tab, enable the Stereo Mix option. Now, "Stereo Mix" is an available microphone option! You can select it as the audio input.
this really helped me! Thank you!
this a grewt idea, i was using voice meeter as a virtual audio thingy and its complicated to use
Great video! Thanks for going through this in such an easy-to-understand way! Can you share the python scripts?
i love your videos man , please video about fastwhisper on docker api please
Hi Kris! I love what you do, I would like to become a member of your channel, but I can't access the page to subscribe, do you have a direct link? the one in description doesn't work for me.. have a good day!
Hey man this is really cool! I'd like to know if you:
1) used the whisper v3 model? or the v2?
2) If you have seen the demos from gpt4, they also showed that gpt ASR is better than whisper v3, wonder if it will be open like whisper.
Impresario thank you
running fully local is one thing ... doing this via webaudio api towards a backend is a different topic - is there any implementation for that as well foreseen?
Interesting stuff on the image creation at the end while talking, not sure if you are taking into consideration puctuation in you sentences? Im pretty sure this would have to do with something cool, maby keeping an overview of all the text that has been moving out of the "buffer" for style ? Looks like something I could have a lot of fun with, do not have the GPU though :/ Colab however.
How does the transcription performance compare to assemblyAI?
Do you think this could be used to transcribe, for example, phone calls made through the browser? I would greatly appreciate your response :)
@Kris : I already joined as an Adept member on Jan 18th 2024 and requested access to the Github Repo via email and also via Discord but have not had any response from you yet ?
what is a transcribe_chunk function in the code? Seems that it's not from faster_whisper?
I have tried to get this to run on M1 MacBook. No joy. The CPU maxes out even with the tiny model. But then I tried with the Whisper.cpp implementation which is compiled for apple silicon. I found a whisper-cpp-python wrapper for that library. That actually runs and is far less CPU bound. It has a bit of a stutter, it is not as clean, it misses words between the chunk processing but you can see that with just a little bit more power it could work.
Hi Seven, could you please share your code with me? Thank you very much!
Would it be possible to do speaker recognition then pipe it into translation
This will be a good tool for language immersion chinese / japanese / indonesian along with the deepl clipboard tool, edge browsers tts engine.
just joined. would be good to get my grubby paws on the files for this.
Is there a way to connect a live streaming url?
does it support speaker diairzation?
That image gen project was pukka!
Has anyone updated the code from the previous video to use this recording method instead?
Hello. I’m beginner in this major. How can I get your code to refer? Thank you
Hi,
Can get the github repo of the above code ?
Thanks
how to get the code for this?
where do i get the setup/python code
i cant find the script of the realtime translation pls help me finding it :((
Kris, you are a genius. Real-time speech transcription can do a lot of things. The last example is great. I can’t wait to watch the video released on Wednesday. My computer is a Mac M chip computer. I found the code in your github and changed it to run on the CPU. Later, some problems occurred, such as incomplete transcribed content and OSError. Can you release a version suitable for Mac computers? grateful
If there any way to translate this text to another languages it will be awesome
How can i get acess to this code?
BROOOO 🎉 FIRST
Waiting for the in deep video :) Btw your discord invite link is expired.
Can I did this with javascript?
Can we get the code used in this video that would be really helpful
Hi, I'm a subscriber but I do not have access to your github ,can you helpme please?
I became a member how do I get access to the code and the github for this
hello :D send me a e-mail at kris@allabtai.com
Can this run on raspberry pi?
Bro can you put th video about live streaming voice to text
how can we download this script?
how to access your sourcecode as a paid channel member?
🧡
I think there's an even faster whisper module but I forget what it's called
Faster whisper and Insanely Fast Whisper don't seem to have AMD gpu support yet. So I had to go with an alternative for the 7900xt. I used wishper.cpp with cuda/HIP + distilled whisper model. Seriously this combination is kinda real-time too, even when using the distil large v2. Though there is a downside to that, the TTS and Whisper on the GPU gobble up like 8GB or vram. This put some limit to the LLM model I can use at same time.
Hey, it's in your video description, therefore easily fixed: the word is "transcription". Why not avoid the irony of a video that extols modern AI voice to text ... transcription ... in which the AI engine will surely avoid this mistake, and at the speed of light.
where can we find the code that you used?
github linked in the description
can it translate?
how can we identify different speakers?
Microsoft co-pilot in a teams call recording transcription. Cant simply call, needs to he a meeting call... subtle difference. Try 'meet now' in teams calender view, or make calendar event.
I might be jaded but... I mean really, how about an AI that calculates the probability of drone attacks or artillery attacks? How about an AI that calculates the probability of soldiers hiding in terrain? I mean, there are already good search algorithms out there, that one may-or-may-not use to carry out artillery strikes. I'm just thinking aloud here. Probably nothing.
Now make it translate and do phone-cals
Noooo…pls nooo. We got plenty auto callers already.
@@rne1223
Where?
where can we get the code
github linked in the description.
could you do another demo to see how it can translate in real time?
yes! there are no really good or fast translation apps available. CZcams auto translate is horrible!
How do we join your community?
Link in desc :) youtube member
@@AllAboutAI just subscribed to your channel but not getting GitHub code..
Can we take source code ?
The sentiment analysis really scares me. I mean, there's absolutely no chance that'll be abused by big tech in terms of political marketing. I mean, like, there's no way in hell right?
iam a member but i cant acces the github pls HELP
this i my github
maxaxaxaxxaxaxaax
Pulling in people with a flashy thumbnail of a Python code that works and then trying to monetize your code based on a library that is already supposed to be open source is in my opinion bs. it is not fair for beginners that might not know Python or whisper very well. for that I give you a thumbs down!
The accuracy sucks. Many words are incorrect which you can see in the image itself.
This isn't usable in the real world.
🎈
Where is the link to this source code ? Thanks amazing
did you get the code
no @@nafila5084
@@nafila5084 Can share the code to me as well?
transcriPtion
Zero latency? I have been check your video timeline. terminal output and audio is not correspond. you must be living a world 1-2 second ahead our timeline. 😅
It is bs to make an open source code monetized! So sorry for you and your kinds... unsubs.
Can you use different languages?
can you tell me the solution of this error : Could not load library cudnn_ops_infer64_8.dll. Error code 126
Please make sure cudnn_ops_infer64_8.dll is in your library path!
try "pip install nvidia-cudnn-cu12"
its didnt work@@user-rs8oo5ro8t
I have registered as a member, please check your email
how to get the code for this?