File size: 2,599 Bytes
8031a8f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
from .vps import calculate_vps # Your file where calc_srs, calculate_pas, calculate_rcs, calculate_vps live
import librosa
import numpy as np
import math
from .filler_analyzer import detect_fillers
def compute_vps_score(file_path: str, whisper_model) -> dict:
"""
Compute VPS (Voice Pacing Score) and its components from a speech sample.
Args:
file_path (str): Path to the audio file.
whisper_model: Transcription model (e.g., OpenAI Whisper or faster-whisper)
Returns:
dict: A dictionary containing VPS, SRS, PAS, RCS, and component scores.
"""
# Transcribe
result = whisper_model.transcribe(file_path)
transcript = result.get("text", "").strip()
segments = result.get("segments", [])
# Validate early
if not transcript or not segments:
raise ValueError("Empty transcript or segments from Whisper.")
# Filler count
filler_count, _ = detect_fillers(transcript)
# Load audio
y, sr = librosa.load(file_path, sr=None)
duration = len(y) / sr if sr else 0.0
if duration <= 0:
raise ValueError("Audio duration invalid or zero.")
# Pitch variation (in semitones)
f0, voiced_flags, voiced_probs = librosa.pyin(
y, sr=sr, fmin=80, fmax=400, frame_length=1024, hop_length=256, fill_na=np.nan)
voiced_f0 = f0[~np.isnan(f0)]
pitch_variation = 0.0
if voiced_f0.size > 0:
median_f0 = np.nanmedian(voiced_f0)
median_f0 = max(median_f0, 1e-6)
semitone_diffs = 12 * np.log2(voiced_f0 / median_f0)
pitch_variation = float(np.nanstd(semitone_diffs))
# Pause analysis
long_pause_count = 0
if segments:
for i in range(len(segments) - 1):
pause_dur = segments[i + 1]["start"] - segments[i]["end"]
if pause_dur > 1.0:
long_pause_count += 1
# Beginning and end
if segments[0]["start"] > 1.0:
long_pause_count += 1
if duration - segments[-1]["end"] > 1.0:
long_pause_count += 1
# WPM
word_count = len(transcript.split())
words_per_min = (word_count / duration) * 60.0 if duration > 0 else 0.0
# Calculate VPS and components
vps_result = calculate_vps(
transcript=transcript,
segments=segments,
filler_count=filler_count,
duration=duration,
wpm=words_per_min,
long_pause_count=long_pause_count,
pitch_variation=pitch_variation,
y=y,
sr=sr
)
# Include transcript optionally
vps_result["transcript"] = transcript
return vps_result
|