52 lines
1.8 KiB
Python
52 lines
1.8 KiB
Python
import sys
|
|
import numpy as np
|
|
import sounddevice as sd
|
|
from transformers import AutoProcessor, CohereAsrForConditionalGeneration
|
|
from transformers.audio_utils import load_audio
|
|
from huggingface_hub import hf_hub_download
|
|
|
|
# Load model
|
|
print("Loading model...")
|
|
processor = AutoProcessor.from_pretrained("CohereLabs/cohere-transcribe-03-2026")
|
|
model = CohereAsrForConditionalGeneration.from_pretrained(
|
|
"CohereLabs/cohere-transcribe-03-2026",
|
|
device_map="auto"
|
|
)
|
|
|
|
def transcribe_audio(audio, language="en"):
|
|
inputs = processor(audio, sampling_rate=16000, return_tensors="pt", language=language)
|
|
inputs.to(model.device, dtype=model.dtype)
|
|
|
|
outputs = model.generate(**inputs, max_new_tokens=256)
|
|
text = processor.decode(outputs, skip_special_tokens=True)
|
|
return text
|
|
|
|
def record_audio(duration, samplerate=16000):
|
|
print(f"Recording for {duration} seconds...")
|
|
audio = sd.rec(int(duration * samplerate), samplerate=samplerate, channels=1, dtype='float32')
|
|
sd.wait()
|
|
return audio.flatten()
|
|
|
|
# Parse arguments
|
|
if len(sys.argv) > 1 and sys.argv[1] == "--mic":
|
|
duration = int(sys.argv[2]) if len(sys.argv) > 2 else 5
|
|
try:
|
|
mic_audio = record_audio(duration)
|
|
print("Transcribing...")
|
|
text = transcribe_audio(mic_audio)
|
|
print(f"\nTranscription:\n{text}\n")
|
|
except OSError as e:
|
|
print(f"Microphone error: {e}")
|
|
print("Hint: Run with nix-shell for PortAudio support")
|
|
else:
|
|
print("Loading demo audio...")
|
|
audio_file = hf_hub_download(
|
|
repo_id="CohereLabs/cohere-transcribe-03-2026",
|
|
filename="demo/voxpopuli_test_en_demo.wav",
|
|
)
|
|
audio = load_audio(audio_file, sampling_rate=16000)
|
|
|
|
print("Transcribing...")
|
|
text = transcribe_audio(audio)
|
|
print(f"\nTranscription:\n{text}\n")
|