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PhilVerify — Whisper ASR Module
Transcribes video/audio files using OpenAI Whisper.
Also provides combined ASR + frame OCR for full video text extraction.
Recommended model: large-v3 (best Filipino speech accuracy).
"""
import asyncio
import logging
import tempfile
import os
logger = logging.getLogger(__name__)
async def transcribe_video(media_bytes: bytes, filename: str = "upload") -> str:
"""
Transcribe audio/video bytes using Whisper.
Saves bytes to a temp file (Whisper requires file path, not bytes).
Returns the transcript string.
"""
try:
import whisper
from config import get_settings
settings = get_settings()
model_size = settings.whisper_model_size
logger.info("Loading Whisper model: %s", model_size)
model = whisper.load_model(model_size)
# Whisper needs a file path — write bytes to temp file
suffix = os.path.splitext(filename)[-1] or ".mp4"
with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
tmp.write(media_bytes)
tmp_path = tmp.name
try:
result = model.transcribe(tmp_path, language=None) # Auto-detect language
transcript = result.get("text", "").strip()
logger.info("Whisper transcribed %d chars (lang=%s)", len(transcript), result.get("language"))
return transcript
finally:
os.unlink(tmp_path) # Clean up temp file
except ImportError:
logger.warning("openai-whisper not installed — ASR unavailable")
return ""
except Exception as e:
logger.error("Whisper transcription failed: %s", e)
return ""
async def transcribe_and_ocr_video(media_bytes: bytes, filename: str = "upload") -> str:
"""
Full video text extraction: runs Whisper ASR and frame OCR in parallel,
then merges results based on what was found.
Cases handled:
- Audio only (no on-screen text) → returns speech transcript alone
- On-screen text only (silent) → returns OCR text alone
- Both → returns labelled combination
- Neither → returns empty string (caller raises 422)
"""
from inputs.video_ocr import extract_text_from_video_frames
# Run Whisper ASR and frame OCR concurrently
speech_text, ocr_text = await asyncio.gather(
transcribe_video(media_bytes, filename=filename),
extract_text_from_video_frames(media_bytes, filename=filename),
)
speech_text = (speech_text or "").strip()
ocr_text = (ocr_text or "").strip()
has_speech = len(speech_text) >= 10
has_ocr = len(ocr_text) >= 10
if has_speech and has_ocr:
logger.info("Video has both speech (%d chars) and on-screen text (%d chars) — combining", len(speech_text), len(ocr_text))
return f"[SPEECH]\n{speech_text}\n\n[ON-SCREEN TEXT]\n{ocr_text}"
if has_speech:
logger.info("Video has speech only (%d chars)", len(speech_text))
return speech_text
if has_ocr:
logger.info("Video has on-screen text only (%d chars)", len(ocr_text))
return ocr_text
logger.warning("Video yielded no usable text from either ASR or frame OCR")
return ""
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