From 06f263b41794b5788c69acf63fd56e3bb0f5fc1b Mon Sep 17 00:00:00 2001
From: YasinOnm08 <onmazyasin4@gmail.com>
Date: Wed, 18 Sep 2024 09:18:50 +0200
Subject: [PATCH] voice recognition with whisper
---
py/voice_recognition.py | 86 +++++++++++++++++++++++++++--------------
1 file changed, 58 insertions(+), 28 deletions(-)
diff --git a/py/voice_recognition.py b/py/voice_recognition.py
index 8ffc199..b9390c5 100644
--- a/py/voice_recognition.py
+++ b/py/voice_recognition.py
@@ -1,31 +1,61 @@
-import speech_recognition as sr
+#pip install faster-whisper
+from api import API
+import os
+import wave
+from faster_whisper import WhisperModel
+import pyaudio
-class Voice: #create Class
- @staticmethod
- def listen(): #define function listen()
- recognizer = sr.Recognizer()
-
- try:
- with sr.Microphone() as source:
- print("Adjusting for ambient noise...")
- recognizer.adjust_for_ambient_noise(source, duration=0.5) #listen to surrounding for .5sec to adjust backgroundnoise
- print("Listening...")
- audio_data = recognizer.listen(source) #listen to user until user stops speaking
- print("Audio captured")
- try:
- text = recognizer.recognize_sphinx(audio_data) # Using Sphinx convert audio to text (also works offline)
- #if any Exceptions or Errors eccur => return ERROR
- except sr.UnknownValueError:
- text = "ERROR"
- except sr.RequestError as e:
- text = "ERROR"
-
- except sr.RequestError as e:
- text = "ERROR"
- except sr.UnknownValueError:
- text = "ERROR"
- except Exception as e:
- text = "ERROR"
- return text
+def transcribe_chunk(model, file_path):
+ print("transcribing...")
+ segments, _ = model.transcribe(file_path)
+ transcription = ""
+ for segment in segments:
+ transcription += segment.text + " "
+ return transcription.strip()
+#Record voice
+#chunk_length = duration to record in seconds
+def record_chunk(p, stream, file_path, chunk_length=2):
+ 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 listen():
+ #model settings (tiny, base, small, medium, large)
+ model_size = "medium"
+ #what should it run on (cpu or cuda for gpu)
+ model = WhisperModel(model_size, device="cpu", compute_type="int8")
+
+ p = pyaudio.PyAudio()
+ stream = p.open(format=pyaudio.paInt16, channels=1, rate = 16000, input = True, frames_per_buffer=1024)
+
+ try:
+ while True:
+ print("Recording...")
+ # CHANGE TEMP FILE PATH
+ chunk_file="temp_chunk.wav"
+ record_chunk(p, stream, chunk_file)
+ transcription = transcribe_chunk(model, chunk_file)
+ print(transcription)
+ try:
+ return transcription
+ except Exception as e:
+ return "ERROR"
+ finally:
+ if os.path.exists(chunk_file):
+ os.remove(chunk_file)
+ break
+ except KeyboardInterrupt:
+ print("Stopping...")
+ finally:
+ stream.stop_stream()
+ stream.close()
+ p.terminate()
\ No newline at end of file